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How People Use Active Telepresence Cameras in Tele-manipulation | https://ieeexplore.ieee.org/document/9561243/ | [
"Tsung-Chi Lin",
"Achyuthan Unni Krishnan",
"Zhi Li",
"Tsung-Chi Lin",
"Achyuthan Unni Krishnan",
"Zhi Li"
] | Robot teleoperation is a reliable way to perform a variety of tasks with complex robotic systems. However, the remote control of active telepresence cameras on the robot for improved telepresence adds an additional degree of complexity while teleoperating and can thus affect the operator’s performance during tele-manipulation. Our previous user study investigates the general human performance and ... |
Social Navigation for Mobile Robots in the Emergency Department | https://ieeexplore.ieee.org/document/9561897/ | [
"Angelique M. Taylor",
"Sachiko Matsumoto",
"Wesley Xiao",
"Laurel D. Riek",
"Angelique M. Taylor",
"Sachiko Matsumoto",
"Wesley Xiao",
"Laurel D. Riek"
] | The emergency department (ED) is a safety-critical environment in which healthcare workers (HCWs) are overburdened, overworked, and have limited resources, especially during the COVID-19 pandemic. One way to address this problem is to explore the use of robots that can support clinical teams, e.g., to deliver materials or restock supplies. However, due to EDs being overcrowded, and the cognitive o... |
Decentralized Structural-RNN for Robot Crowd Navigation with Deep Reinforcement Learning | https://ieeexplore.ieee.org/document/9561595/ | [
"Shuijing Liu",
"Peixin Chang",
"Weihang Liang",
"Neeloy Chakraborty",
"Katherine Driggs-Campbell",
"Shuijing Liu",
"Peixin Chang",
"Weihang Liang",
"Neeloy Chakraborty",
"Katherine Driggs-Campbell"
] | Safe and efficient navigation through human crowds is an essential capability for mobile robots. Previous work on robot crowd navigation assumes that the dynamics of all agents are known and well-defined. In addition, the performance of previous methods deteriorates in partially observable environments and environments with dense crowds. To tackle these problems, we propose decentralized structura... |
Range Limited Coverage Control using Air-Ground Multi-Robot Teams | https://ieeexplore.ieee.org/document/9561706/ | [
"Max Rudolph",
"Sean Wilson",
"Magnus Egerstedt",
"Max Rudolph",
"Sean Wilson",
"Magnus Egerstedt"
] | In this paper, we investigate how heterogeneous multi-robot systems with different sensing capabilities can observe a domain with an a priori unknown density function. Common coverage control techniques are targeted towards homogeneous teams of robots and do not consider what happens when the sensing capabilities of the robots are vastly different. This work proposes an extension to Lloyd’s algori... |
Communication Strategy for Efficient Guidance Providing : Domain-structure Awareness, Performance Trade-offs, and Value of Future Observations | https://ieeexplore.ieee.org/document/9561880/ | [
"Shih-Yun Lo",
"Andrea L. Thomaz",
"Shih-Yun Lo",
"Andrea L. Thomaz"
] | Service robots are gaining capabilities to be deployed in public environments for human assistance. While robot actively providing guidance has shown great success in field study, the communication strategy (the strategy to decide whom to initiate the service for and when), and hence the performance evaluation, has been based on behavioral-based qualitative analysis. We attribute this to the chall... |
LBGP: Learning Based Goal Planning for Autonomous Following in Front | https://ieeexplore.ieee.org/document/9560914/ | [
"Payam Nikdel",
"Richard Vaughan",
"Mo Chen",
"Payam Nikdel",
"Richard Vaughan",
"Mo Chen"
] | This paper investigates a hybrid solution which combines deep reinforcement learning (RL) and classical trajectory planning for the "following in front" application. Here, an autonomous robot aims to stay ahead of a person as the person freely walks around. Following in front is a challenging problem as the user’s intended trajectory is unknown and needs to be estimated, explicitly or implicitly, ... |
Reactive Human-to-Robot Handovers of Arbitrary Objects | https://ieeexplore.ieee.org/document/9561170/ | [
"Wei Yang",
"Chris Paxton",
"Arsalan Mousavian",
"Yu-Wei Chao",
"Maya Cakmak",
"Dieter Fox",
"Wei Yang",
"Chris Paxton",
"Arsalan Mousavian",
"Yu-Wei Chao",
"Maya Cakmak",
"Dieter Fox"
] | Human-robot object handovers have been an actively studied area of robotics over the past decade; however, very few techniques and systems have addressed the challenge of handing over diverse objects with arbitrary appearance, size, shape, and deformability. In this paper, we present a vision-based system that enables reactive human-to-robot handovers of unknown objects. Our approach combines clos... |
Smile Like You Mean It: Driving Animatronic Robotic Face with Learned Models | https://ieeexplore.ieee.org/document/9560797/ | [
"Boyuan Chen",
"Yuhang Hu",
"Lianfeng Li",
"Sara Cummings",
"Hod Lipson",
"Boyuan Chen",
"Yuhang Hu",
"Lianfeng Li",
"Sara Cummings",
"Hod Lipson"
] | Ability to generate intelligent and generalizable facial expressions is essential for building human-like social robots. At present, progress in this field is hindered by the fact that each facial expression needs to be programmed by humans. In order to adapt robot behavior in real time to different situations that arise when interacting with human subjects, robots need to be able to train themsel... |
I Know What You Meant: Learning Human Objectives by (Under)estimating Their Choice Set | https://ieeexplore.ieee.org/document/9562048/ | [
"Ananth Jonnavittula",
"Dylan P. Losey",
"Ananth Jonnavittula",
"Dylan P. Losey"
] | Assistive robots have the potential to help people perform everyday tasks. However, these robots first need to learn what it is their user wants them to do. Teaching assistive robots is hard for inexperienced users, elderly users, and users living with physical disabilities, since often these individuals are unable to show the robot their desired behavior. We know that inclusive learners should gi... |
Analyzing Human Models that Adapt Online | https://ieeexplore.ieee.org/document/9561652/ | [
"Andrea Bajcsy",
"Anand Siththaranjan",
"Claire J. Tomlin",
"Anca D. Dragan",
"Andrea Bajcsy",
"Anand Siththaranjan",
"Claire J. Tomlin",
"Anca D. Dragan"
] | Predictive human models often need to adapt their parameters online from human data. This raises previously ignored safety-related questions for robots relying on these models such as what the model could learn online and how quickly could it learn it. For instance, when will the robot have a confident estimate in a nearby human’s goal? Or, what parameter initializations guarantee that the robot c... |
When Shall I Be Empathetic? The Utility of Empathetic Parameter Estimation in Multi-Agent Interactions | https://ieeexplore.ieee.org/document/9561079/ | [
"Yi Chen",
"Lei Zhang",
"Tanner Merry",
"Sunny Amatya",
"Wenlong Zhang",
"Yi Ren",
"Yi Chen",
"Lei Zhang",
"Tanner Merry",
"Sunny Amatya",
"Wenlong Zhang",
"Yi Ren"
] | Human-robot interactions (HRI) can be modeled as differential games with incomplete information, where each agent holds private reward parameters. Due to the open challenge in finding perfect Bayesian equilibria of such games, existing studies often decouple the belief and physical dynamics by iterating between belief update and motion planning. Importantly, the robot’s reward parameters are often... |
Three-dimensional Terrain Aware Autonomous Exploration for Subterranean and Confined Spaces | https://ieeexplore.ieee.org/document/9561099/ | [
"Héctor Azpúrua",
"Mario F. M. Campos",
"Douglas G. Macharet",
"Héctor Azpúrua",
"Mario F. M. Campos",
"Douglas G. Macharet"
] | Despite the advances in autonomous navigation and motion planning, there are still several challenges to overcome, especially for confined or underground spaces. Confined scenarios present challenges such as lack of global or accurate external localization, uneven and slippery terrains, and multilevel stages. Exploring and mapping unknown unstructured environments is a fundamental step into the sa... |
Semantically-Aware Strategies for Stereo-Visual Robotic Obstacle Avoidance | https://ieeexplore.ieee.org/document/9561863/ | [
"Jungseok Hong",
"Karin de Langis",
"Cole Wyethv",
"Christopher Walaszek",
"Junaed Sattar",
"Jungseok Hong",
"Karin de Langis",
"Cole Wyethv",
"Christopher Walaszek",
"Junaed Sattar"
] | Mobile robots in unstructured, mapless environments must rely on an obstacle avoidance module to navigate safely. The standard avoidance techniques estimate the locations of obstacles with respect to the robot but are unaware of the obstacles’ identities. Consequently, the robot cannot take advantage of semantic information about obstacles when making decisions about how to navigate. We propose an... |
LiDARNet: A Boundary-Aware Domain Adaptation Model for Point Cloud Semantic Segmentation | https://ieeexplore.ieee.org/document/9561255/ | [
"Peng Jiang",
"Srikanth Saripalli",
"Peng Jiang",
"Srikanth Saripalli"
] | We present a boundary-aware domain adaptation model for LiDAR scan full-scene semantic segmentation (LiDARNet). Our model can extract both the domain private features and the domain shared features with a two branch structure. We embedded Gated-SCNN into the segmentor component of LiDARNet to learn boundary information while learning to predict full-scene semantic segmentation labels. Moreover, we... |
Transition Motion Planning for Multi-Limbed Vertical Climbing Robots Using Complementarity Constraints | https://ieeexplore.ieee.org/document/9562014/ | [
"Jingwen Zhang",
"Xuan Lin",
"Dennis W Hong",
"Jingwen Zhang",
"Xuan Lin",
"Dennis W Hong"
] | In order to achieve autonomous vertical wall climbing, the transition phase from the ground to the wall requires extra consideration inevitably. This paper focuses on the contact sequence planner to transition between flat terrain and vertical surfaces for multi-limbed climbing robots. To overcome the transition phase, it requires planning both multicontact and contact wrenches simultaneously whic... |
Inverse Dynamics Control of Compliant Hybrid Zero Dynamic Walking | https://ieeexplore.ieee.org/document/9560906/ | [
"Jenna Reher",
"Aaron D. Ames",
"Jenna Reher",
"Aaron D. Ames"
] | We present a trajectory planning and control architecture for bipedal locomotion at a variety of speeds on a highly underactuated and compliant bipedal robot. A library of compliant walking trajectories are planned offline, and stored as compact arrays of polynomial coefficients for tracking online. The control implementation uses a floating-base inverse dynamics controller which generates dynamic... |
The dynamic effect of mechanical losses of transmissions on the equation of motion of legged robots | https://ieeexplore.ieee.org/document/9561739/ | [
"Youngwoo Sim",
"Joao Ramos",
"Youngwoo Sim",
"Joao Ramos"
] | Industrial manipulators do not collapse under their own weight when powered off due to the friction in their joints. Although these mechanism are effective for stiff position control of pick-and-place, they are inappropriate for legged robots that must rapidly regulate compliant interactions with the environment. However, no metric exists to quantify the robot’s performance degradation due to mech... |
Stabilizing Neural Control Using Self-Learned Almost Lyapunov Critics | https://ieeexplore.ieee.org/document/9560886/ | [
"Ya-Chien Chang",
"Sicun Gao",
"Ya-Chien Chang",
"Sicun Gao"
] | The lack of stability guarantee restricts the practical use of learning-based methods in core control problems in robotics. We develop new methods for learning neural control policies and neural Lyapunov critic functions in the modelfree reinforcement learning (RL) setting. We use sample-based approaches and the Almost Lyapunov function conditions to estimate the region of attraction and invarianc... |
Regularizing Action Policies for Smooth Control with Reinforcement Learning | https://ieeexplore.ieee.org/document/9561138/ | [
"Siddharth Mysore",
"Bassel Mabsout",
"Renato Mancuso",
"Kate Saenko",
"Siddharth Mysore",
"Bassel Mabsout",
"Renato Mancuso",
"Kate Saenko"
] | A critical problem with the practical utility of controllers trained with deep Reinforcement Learning (RL) is the notable lack of smoothness in the actions learned by the RL policies. This trend often presents itself in the form of control signal oscillation and can result in poor control, high power consumption, and undue system wear. We introduce Conditioning for Action Policy Smoothness (CAPS),... |
DeepReach: A Deep Learning Approach to High-Dimensional Reachability | https://ieeexplore.ieee.org/document/9561949/ | [
"Somil Bansal",
"Claire J. Tomlin",
"Somil Bansal",
"Claire J. Tomlin"
] | Hamilton-Jacobi (HJ) reachability analysis is an important formal verification method for guaranteeing performance and safety properties of dynamical control systems. Its advantages include compatibility with general nonlinear system dynamics, formal treatment of bounded disturbances, and the ability to deal with state and input constraints. However, it involves solving a PDE, whose computational ... |
Deep Reinforcement Learning for Active Target Tracking | https://ieeexplore.ieee.org/document/9561258/ | [
"Heejin Jeong",
"Hamed Hassani",
"Manfred Morari",
"Daniel D. Lee",
"George J. Pappas",
"Heejin Jeong",
"Hamed Hassani",
"Manfred Morari",
"Daniel D. Lee",
"George J. Pappas"
] | We solve active target tracking, one of the essential tasks in autonomous systems, using a deep reinforcement learning (RL) approach. In this problem, an autonomous agent is tasked with acquiring information about targets of interests using its on-board sensors. The classical challenges in this problem are system model dependence and the difficulty of computing information-theoretic cost functions... |
Deep Reinforcement Learning for Mapless Navigation of a Hybrid Aerial Underwater Vehicle with Medium Transition | https://ieeexplore.ieee.org/document/9561188/ | [
"Ricardo B. Grando",
"Junior C. de Jesus",
"Victor A. Kich",
"Alisson H. Kolling",
"Nicolas P. Bortoluzzi",
"Pedro M. Pinheiro",
"Armando A. Neto",
"Paulo L. J. Drews",
"Ricardo B. Grando",
"Junior C. de Jesus",
"Victor A. Kich",
"Alisson H. Kolling",
"Nicolas P. Bortoluzzi",
"Pedro M. Pinheiro",
"Armando A. Neto",
"Paulo L. J. Drews"
] | Since the application of Deep Q-Learning to the continuous action domain in Atari-like games, Deep Reinforcement Learning (Deep-RL) techniques for motion control have been qualitatively enhanced. Nowadays, modern Deep-RL can be successfully applied to solve a wide range of complex decision-making tasks for many types of vehicles. Based on this context, in this paper, we propose the use of Deep-RL ... |
NF-iSAM: Incremental Smoothing and Mapping via Normalizing Flows | https://ieeexplore.ieee.org/document/9561436/ | [
"Qiangqiang Huang",
"Can Pu",
"Dehann Fourie",
"Kasra Khosoussi",
"Jonathan P. How",
"John J. Leonard",
"Qiangqiang Huang",
"Can Pu",
"Dehann Fourie",
"Kasra Khosoussi",
"Jonathan P. How",
"John J. Leonard"
] | This paper presents a novel non-Gaussian inference algorithm, Normalizing Flow iSAM (NF-iSAM), for solving SLAM problems with non-Gaussian factors and/or non-linear measurement models. NF-iSAM exploits the expressive power of neural networks, and trains normalizing flows to draw samples from the joint posterior of non-Gaussian factor graphs. By leveraging the Bayes tree, NF-iSAM is able to exploit... |
UPSLAM: Union of Panoramas SLAM | https://ieeexplore.ieee.org/document/9561962/ | [
"Anthony Cowley",
"Ian D. Miller",
"Camillo Jose Taylor",
"Anthony Cowley",
"Ian D. Miller",
"Camillo Jose Taylor"
] | We present an empirical investigation of a new mapping system based on a graph of panoramic depth images. Panoramic images efficiently capture range measurements taken by a spinning lidar sensor, recording fine detail on the order of a few centimeters within maps of expansive scope on the order of tens of millions of cubic meters. The flexibility of the system is demonstrated by running the same map... |
RELLIS-3D Dataset: Data, Benchmarks and Analysis | https://ieeexplore.ieee.org/document/9561251/ | [
"Peng Jiang",
"Philip Osteen",
"Maggie Wigness",
"Srikanth Saripalli",
"Peng Jiang",
"Philip Osteen",
"Maggie Wigness",
"Srikanth Saripalli"
] | Semantic scene understanding is crucial for robust and safe autonomous navigation, particularly so in off-road environments. Recent deep learning advances for 3D semantic segmentation rely heavily on large sets of training data, however existing autonomy datasets either represent urban environments or lack multimodal off-road data. We fill this gap with RELLIS-3D, a multimodal dataset collected in... |
Model-based Reinforcement Learning with Provable Safety Guarantees via Control Barrier Functions | https://ieeexplore.ieee.org/document/9561253/ | [
"Hongchao Zhang",
"Zhouchi Li",
"Andrew Clark",
"Hongchao Zhang",
"Zhouchi Li",
"Andrew Clark"
] | Safety is a critical property in applications including robotics, transportation, and energy. Safety is especially challenging in reinforcement learning (RL) settings, in which uncertainty of the system dynamics may cause safety violations during exploration. Control Barrier Functions (CBFs), which enforce safety by constraining the control actions at each time step, are a promising approach for s... |
Continual Model-Based Reinforcement Learning with Hypernetworks | https://ieeexplore.ieee.org/document/9560793/ | [
"Yizhou Huang",
"Kevin Xie",
"Homanga Bharadhwaj",
"Florian Shkurti",
"Yizhou Huang",
"Kevin Xie",
"Homanga Bharadhwaj",
"Florian Shkurti"
] | Effective planning in model-based reinforcement learning (MBRL) and model-predictive control (MPC) relies on the accuracy of the learned dynamics model. In many instances of MBRL and MPC, this model is assumed to be stationary and is periodically re-trained from scratch on state transition experience collected from the beginning of environment interactions. This implies that the time required to t... |
Reinforcement Learning Based Temporal Logic Control with Maximum Probabilistic Satisfaction | https://ieeexplore.ieee.org/document/9561903/ | [
"Mingyu Cai",
"Shaoping Xiao",
"Baoluo Li",
"Zhiliang Li",
"Zhen Kan",
"Mingyu Cai",
"Shaoping Xiao",
"Baoluo Li",
"Zhiliang Li",
"Zhen Kan"
] | This paper presents a model-free reinforcement learning (RL) algorithm to synthesize a control policy that maximizes the satisfaction probability of complex tasks, which are expressed by linear temporal logic (LTL) specifications. Due to the consideration of environment and motion uncertainties, we model the robot motion as a probabilistic labeled Markov decision process (PL-MDP) with unknown tran... |
Solving Markov Decision Processes with Partial State Abstractions | https://ieeexplore.ieee.org/document/9561435/ | [
"Samer B. Nashed",
"Justin Svegliato",
"Matteo Brucato",
"Connor Basich",
"Rod Grupen",
"Shlomo Zilberstein",
"Samer B. Nashed",
"Justin Svegliato",
"Matteo Brucato",
"Connor Basich",
"Rod Grupen",
"Shlomo Zilberstein"
] | Autonomous systems often use approximate planners that exploit state abstractions to solve large MDPs in real-time decision-making problems. However, these planners can eliminate details needed to produce effective behavior in autonomous systems. We therefore propose a novel model, a partially abstract MDP, with a set of abstract states that each compress a set of ground states to condense irrelev... |
CVaR-based Flight Energy Risk Assessment for Multirotor UAVs using a Deep Energy Model | https://ieeexplore.ieee.org/document/9561658/ | [
"Arnav Choudhry",
"Brady Moon",
"Jay Patrikar",
"Constantine Samaras",
"Sebastian Scherer",
"Arnav Choudhry",
"Brady Moon",
"Jay Patrikar",
"Constantine Samaras",
"Sebastian Scherer"
] | Energy management is a critical aspect of risk assessment for Uncrewed Aerial Vehicle (UAV) flights, as a depleted battery during a flight brings almost guaranteed vehicle damage and a high risk of human injuries or property damage. Predicting the amount of energy a flight will consume is challenging as routing, weather, obstacles, and other factors affect the overall consumption. We develop a dee... |
Hypergame-based Adaptive Behavior Path Planning for Combined Exploration and Visual Search | https://ieeexplore.ieee.org/document/9561451/ | [
"Mihir Dharmadhikari",
"Harshal Deshpande",
"Tung Dang",
"Kostas Alexis",
"Mihir Dharmadhikari",
"Harshal Deshpande",
"Tung Dang",
"Kostas Alexis"
] | In this work, we present an adaptive behavior path planning method for autonomous exploration and visual search of unknown environments. As volumetric exploration and visual coverage of unknown environments, with possibly different sensors, are non-identical objectives, a principled combination of the two is proposed. In particular, the method involves three distinct planning policies, namely expl... |
Morphologically Adapatative Quad-Rotor Towards Acquiring High-Performance Flight: A Comparative Study and Validation | https://ieeexplore.ieee.org/document/9560667/ | [
"Na Zhao",
"Weixin Yang",
"Cong Peng",
"Gang Wang",
"Yantao Shen",
"Na Zhao",
"Weixin Yang",
"Cong Peng",
"Gang Wang",
"Yantao Shen"
] | This paper presents our comparative study on how the flight performances of an in-flight morphing quad-rotor are affected by the morph induced inertia variation. A custom-built in-flight morphing quad-rotor was employed in numerical and experimental tests for the study and analysis. In these tests, the quad-rotor is controlled to follow a predefined path and/or to hover in an environment with the ... |
Beelines: Motion Prediction Metrics for Self-Driving Safety and Comfort | https://ieeexplore.ieee.org/document/9560950/ | [
"Skanda Shridhar",
"Yuhang Ma",
"Tara Stentz",
"Zhengdi Shen",
"Galen Clark Haynes",
"Neil Traft",
"Skanda Shridhar",
"Yuhang Ma",
"Tara Stentz",
"Zhengdi Shen",
"Galen Clark Haynes",
"Neil Traft"
] | The commonly used metrics for motion prediction do not correlate well with a self-driving vehicle’s system-level performance. The most common metrics are average displacement error (ADE) and final displacement error (FDE), which omit many features, making them poor self-driving performance indicators. Since high-fidelity simulations and track testing can be resource-intensive, the use of predictio... |
Performance Metrics Calculation for Assembly Systems with Exponential Reliability Machines | https://ieeexplore.ieee.org/document/9561947/ | [
"Yishu Bai",
"Liang Zhang",
"Yishu Bai",
"Liang Zhang"
] | Assembly systems are commonly seen in production practice, where multiple components are joined in a manufacturing process to make a final product. In this paper, a decomposition/aggregation-based method is presented to evaluate the performance metrics of assembly systems with machines following the exponential reliability model (either synchronous or asynchronous). In particular, we consider the ... |
Learning Seed Placements and Automation Policies for Polyculture Farming with Companion Plants | https://ieeexplore.ieee.org/document/9561431/ | [
"Yahav Avigal",
"Anna Deza",
"William Wong",
"Sebastian Oehme",
"Mark Presten",
"Mark Theis",
"Jackson Chui",
"Paul Shao",
"Huang Huang",
"Atsunobu Kotani",
"Satvik Sharma",
"Rishi Parikh",
"Michael Luo",
"Sandeep Mukherjee",
"Stefano Carpin",
"Joshua H. Viers",
"Stavros Vougioukas",
"Ken Goldberg",
"Yahav Avigal",
"Anna Deza",
"William Wong",
"Sebastian Oehme",
"Mark Presten",
"Mark Theis",
"Jackson Chui",
"Paul Shao",
"Huang Huang",
"Atsunobu Kotani",
"Satvik Sharma",
"Rishi Parikh",
"Michael Luo",
"Sandeep Mukherjee",
"Stefano Carpin",
"Joshua H. Viers",
"Stavros Vougioukas",
"Ken Goldberg"
] | Polyculture farming is a sustainable farming technique based on synergistic interactions between differing plant types that make them more resistant to diseases and pests and better able to retain water. Reduced uniformity can reduce use of pesticides, fertilizer, and water, but is more labor intensive and more challenging to automate. We describe a scaled physical testbed (1.5m×3.0m) that uses a ... |
A General-Purpose Anomalous Scenario Synthesizer for Rotary Equipment | https://ieeexplore.ieee.org/document/9561841/ | [
"Yip Fun Yeung",
"Ali Alshehri",
"Lois Wampler",
"Mikio Furokawa",
"Takayuki Hirano",
"Kamal Youcef-Toumi",
"Yip Fun Yeung",
"Ali Alshehri",
"Lois Wampler",
"Mikio Furokawa",
"Takayuki Hirano",
"Kamal Youcef-Toumi"
] | Data synthesizing is crucial for data-driven anomaly prognostics on physical machines. We propose the first general-purpose anomalous scenario synthesizer, GPASS, for rotary equipment. More specifically, we present a design of implementing modular rotational damping, large lateral force, with high-frequency range capability as fundamental modes of physical inputs. The GPASS is a general-purpose pl... |
An Autonomous Vault-Building Robot System for Creating Spanning Structures | https://ieeexplore.ieee.org/document/9561004/ | [
"Nathan Melenbrink",
"Ariel Wang",
"Justin Werfel",
"Nathan Melenbrink",
"Ariel Wang",
"Justin Werfel"
] | Research in autonomous robots for construction has largely focused on ground-based robots whose reach constrains the size of what they can build, or on climbing or aerial robots that build solid or unroofed structures. Autonomous construction of larger, multistory buildings, or bridges spanning unsupported distances, would require robots that build sturdy structures supporting their own weight. In... |
Towards the Unification of System Design and Motion Synthesis for High-Performance Hopping Robots | https://ieeexplore.ieee.org/document/9561322/ | [
"Eric Ambrose",
"Wen-Loong Ma",
"Aaron D. Ames",
"Eric Ambrose",
"Wen-Loong Ma",
"Aaron D. Ames"
] | Robotic hopping requires high performance and precision, due to its extreme interactions with the environment. Designing a system that will perform optimally, or even stably, for this motion primitive is a significant challenge. In previous work, it was shown that designing a robot with two springs (one in series and one in parallel with the actuator) could dramatically improve performance. Howeve... |
Multi-Step Recurrent Q-Learning for Robotic Velcro Peeling | https://ieeexplore.ieee.org/document/9561030/ | [
"Jiacheng Yuan",
"Nicolai Häni",
"Volkan Isler",
"Jiacheng Yuan",
"Nicolai Häni",
"Volkan Isler"
] | Learning object manipulation is a critical skill for robots to interact with their environment. Even though there has been significant progress in robotic manipulation of rigid objects, interacting with non-rigid objects remains challenging for robots. In this work, we introduce velcro peeling as a new application for robotic manipulation of non-rigid objects in complex environments. We present a ... |
Reset-Free Reinforcement Learning via Multi-Task Learning: Learning Dexterous Manipulation Behaviors without Human Intervention | https://ieeexplore.ieee.org/document/9561384/ | [
"Abhishek Gupta",
"Justin Yu",
"Tony Z. Zhao",
"Vikash Kumar",
"Aaron Rovinsky",
"Kelvin Xu",
"Thomas Devlin",
"Sergey Levine",
"Abhishek Gupta",
"Justin Yu",
"Tony Z. Zhao",
"Vikash Kumar",
"Aaron Rovinsky",
"Kelvin Xu",
"Thomas Devlin",
"Sergey Levine"
] | Reinforcement Learning (RL) algorithms can in principle acquire complex robotic skills by learning from large amounts of data in the real world, collected via trial and error. However, most RL algorithms use a carefully engineered setup in order to collect data, requiring human supervision and intervention to provide episodic resets. This is particularly evident in challenging robotics problems, s... |
Model Predictive Actor-Critic: Accelerating Robot Skill Acquisition with Deep Reinforcement Learning | https://ieeexplore.ieee.org/document/9561298/ | [
"Andrew S. Morgan",
"Daljeet Nandha",
"Georgia Chalvatzaki",
"Carlo D’Eramo",
"Aaron M. Dollar",
"Jan Peters",
"Andrew S. Morgan",
"Daljeet Nandha",
"Georgia Chalvatzaki",
"Carlo D’Eramo",
"Aaron M. Dollar",
"Jan Peters"
] | Substantial advancements to model-based reinforcement learning algorithms have been impeded by the model-bias induced by the collected data, which generally hurts performance. Meanwhile, their inherent sample efficiency warrants utility for most robot applications, limiting potential damage to the robot and its environment during training. Inspired by information theoretic model predictive control... |
Robotic Slicing of Fruits and Vegetables: Modeling the Effects of Fracture Toughness and Knife Geometry | https://ieeexplore.ieee.org/document/9560761/ | [
"Prajjwal Jamdagni",
"Yan-Bin Jia",
"Prajjwal Jamdagni",
"Yan-Bin Jia"
] | Slicing is an important skill for a robot to learn as it is more efficient and results in less deformation in comparison with cutting by pressing. Cutting experiments with foods have indicated that the ease of slicing is caused by a decrease in fracture toughness. In this paper, we formally characterize this decrease based on the work needed to maintain the critical strain for fracture. Forces gen... |
Auto-Tuned Sim-to-Real Transfer | https://ieeexplore.ieee.org/document/9562091/ | [
"Yuqing Du",
"Olivia Watkins",
"Trevor Darrell",
"Pieter Abbeel",
"Deepak Pathak",
"Yuqing Du",
"Olivia Watkins",
"Trevor Darrell",
"Pieter Abbeel",
"Deepak Pathak"
] | Policies trained in simulation often fail when transferred to the real world due to the ‘reality gap’ where the simulator is unable to accurately capture the dynamics and visual properties of the real world. Current approaches to tackle this problem, such as domain randomization, require prior knowledge and engineering to determine how much to randomize system parameters in order to learn a policy... |
A Convex Quasistatic Time-stepping Scheme for Rigid Multibody Systems with Contact and Friction | https://ieeexplore.ieee.org/document/9560941/ | [
"Tao Pang",
"Russ Tedrake",
"Tao Pang",
"Russ Tedrake"
] | Motion planning for robotic manipulation makes heavy use of quasistatic models, but these same models have not yet proven useful for simulation. This is because in many multi-contact situations, the quasistatic models do not describe a unique next state for the system. A planner is able to use these models optimistically (checking only for feasibility of a motion), but simulation requires more.In ... |
Uniform Object Rearrangement: From Complete Monotone Primitives to Efficient Non-Monotone Informed Search | https://ieeexplore.ieee.org/document/9561716/ | [
"Rui Wang",
"Kai Gao",
"Daniel Nakhimovich",
"Jingjin Yu",
"Kostas E. Bekris",
"Rui Wang",
"Kai Gao",
"Daniel Nakhimovich",
"Jingjin Yu",
"Kostas E. Bekris"
] | Object rearrangement is a widely-applicable and challenging task for robots. Geometric constraints must be carefully examined to avoid collisions and combinatorial issues arise as the number of objects increases. This work studies the algorithmic structure of rearranging uniform objects, where robot-object collisions do not occur but object-object collisions have to be avoided. The objective is mi... |
RASCAL: Robotic Arm for Sherds and Ceramics Automated Locomotion | https://ieeexplore.ieee.org/document/9561057/ | [
"Deborah Wang",
"Brandon Lutz",
"Peter J. Cobb",
"Philip Dames",
"Deborah Wang",
"Brandon Lutz",
"Peter J. Cobb",
"Philip Dames"
] | Ceramics are one of the major sources of information about the past for archaeologists, with a typical archaeological dig unearthing 1000’s of pottery fragments (sherds) each day. However, archaeologists often are not allowed to remove these sherds from their home countries. Therefore, logging data (e.g., mass, color, decoration) in the field is the only way to record valuable information about th... |
Reactive Planning for Mobile Manipulation Tasks in Unexplored Semantic Environments | https://ieeexplore.ieee.org/document/9561958/ | [
"Vasileios Vasilopoulos",
"Yiannis Kantaros",
"George J. Pappas",
"Daniel E. Koditschek",
"Vasileios Vasilopoulos",
"Yiannis Kantaros",
"George J. Pappas",
"Daniel E. Koditschek"
] | Complex manipulation tasks, such as rearrangement planning of numerous objects, are combinatorially hard problems. Existing algorithms either do not scale well or assume a great deal of prior knowledge about the environment, and few offer any rigorous guarantees. In this paper, we propose a novel hybrid control architecture for achieving such tasks with mobile manipulators. On the discrete side, w... |
Arm-Hand Systems As Hybrid Parallel-Serial Systems: A Novel Inverse Kinematics Solution | https://ieeexplore.ieee.org/document/9561414/ | [
"Shuwei Qiu",
"Mehrdad R. Kermani",
"Shuwei Qiu",
"Mehrdad R. Kermani"
] | In this paper, we aim to solve inverse kinematics of the integrated robotic arm-hand systems to achieve precision grasping, provided the desired grasp configuration (contact points + contact normals). The key insights of our approach are three-fold. First, we propose a human-inspired thumb-first strategy and consider one finger of the robotic hand as the "thumb" to narrow down the search space and... |
Tactile-RL for Insertion: Generalization to Objects of Unknown Geometry | https://ieeexplore.ieee.org/document/9561646/ | [
"Siyuan Dong",
"Devesh K. Jha",
"Diego Romeres",
"Sangwoon Kim",
"Daniel Nikovski",
"Alberto Rodriguez",
"Siyuan Dong",
"Devesh K. Jha",
"Diego Romeres",
"Sangwoon Kim",
"Daniel Nikovski",
"Alberto Rodriguez"
] | Object insertion is a classic contact-rich manipulation task. The task remains challenging, especially when considering general objects of unknown geometry, which significantly limits the ability to understand the contact configuration between the object and the environment. We study the problem of aligning the object and environment with a tactile-based feedback insertion policy. The insertion pr... |
Sim-to-Real for Robotic Tactile Sensing via Physics-Based Simulation and Learned Latent Projections | https://ieeexplore.ieee.org/document/9561969/ | [
"Yashraj Narang",
"Balakumar Sundaralingam",
"Miles Macklin",
"Arsalan Mousavian",
"Dieter Fox",
"Yashraj Narang",
"Balakumar Sundaralingam",
"Miles Macklin",
"Arsalan Mousavian",
"Dieter Fox"
] | Tactile sensing is critical for robotic grasping and manipulation of objects under visual occlusion. However, in contrast to simulations of robot arms and cameras, current simulations of tactile sensors have limited accuracy, speed, and utility. In this work, we develop an efficient 3D finite element method (FEM) model of the SynTouch BioTac sensor using an open-access, GPU-based robotics simulato... |
Tactile SLAM: Real-time inference of shape and pose from planar pushing | https://ieeexplore.ieee.org/document/9562060/ | [
"Sudharshan Suresh",
"Maria Bauza",
"Kuan-Ting Yu",
"Joshua G. Mangelson",
"Alberto Rodriguez",
"Michael Kaess",
"Sudharshan Suresh",
"Maria Bauza",
"Kuan-Ting Yu",
"Joshua G. Mangelson",
"Alberto Rodriguez",
"Michael Kaess"
] | Tactile perception is central to robot manipulation in unstructured environments. However, it requires contact, and a mature implementation must infer object models while also accounting for the motion induced by the interaction. In this work, we present a method to estimate both object shape and pose in real-time from a stream of tactile measurements. This is applied towards tactile exploration o... |
APPLI: Adaptive Planner Parameter Learning From Interventions | https://ieeexplore.ieee.org/document/9561311/ | [
"Zizhao Wang",
"Xuesu Xiao",
"Bo Liu",
"Garrett Warnell",
"Peter Stone",
"Zizhao Wang",
"Xuesu Xiao",
"Bo Liu",
"Garrett Warnell",
"Peter Stone"
] | While classical autonomous navigation systems can typically move robots from one point to another safely and in a collision-free manner, these systems may fail or produce suboptimal behavior in certain scenarios. The current practice in such scenarios is to manually re-tune the system’s parameters, e.g. max speed, sampling rate, inflation radius, to optimize performance. This practice requires exp... |
APPLR: Adaptive Planner Parameter Learning from Reinforcement | https://ieeexplore.ieee.org/document/9561647/ | [
"Zifan Xu",
"Gauraang Dhamankar",
"Anirudh Nair",
"Xuesu Xiao",
"Garrett Warnell",
"Bo Liu",
"Zizhao Wang",
"Peter Stone",
"Zifan Xu",
"Gauraang Dhamankar",
"Anirudh Nair",
"Xuesu Xiao",
"Garrett Warnell",
"Bo Liu",
"Zizhao Wang",
"Peter Stone"
] | Classical navigation systems typically operate using a fixed set of hand-picked parameters (e.g. maximum speed, sampling rate, inflation radius, etc.) and require heavy expert re-tuning in order to work in new environments. To mitigate this requirement, it has been proposed to learn parameters for different contexts in a new environment using human demonstrations collected via teleoperation. Howev... |
Reinforced iLQR: A Sample-Efficient Robot Locomotion Learning | https://ieeexplore.ieee.org/document/9561223/ | [
"Tongyu Zong",
"Liyang Sun",
"Yong Liu",
"Tongyu Zong",
"Liyang Sun",
"Yong Liu"
] | Robot locomotion is a major challenge in robotics. Model-based approaches are vulnerable to model errors, and incur high computation overhead resulted from long control horizon. Model-free approaches are trained with a large number of training samples, which are expensive to obtain. In this paper, we develop a hybrid control and learning framework, called Reinforced iLQR (RiLQR), which combines th... |
Learning Multi-Arm Manipulation Through Collaborative Teleoperation | https://ieeexplore.ieee.org/document/9561491/ | [
"Albert Tung",
"Josiah Wong",
"Ajay Mandlekar",
"Roberto Martín-Martín",
"Yuke Zhu",
"Li Fei-Fei",
"Silvio Savarese",
"Albert Tung",
"Josiah Wong",
"Ajay Mandlekar",
"Roberto Martín-Martín",
"Yuke Zhu",
"Li Fei-Fei",
"Silvio Savarese"
] | Imitation Learning (IL) is a powerful paradigm to teach robots to perform manipulation tasks by allowing them to learn from human demonstrations collected via teleoperation, but has mostly been limited to single-arm manipulation. However, many real-world tasks require multiple arms, such as lifting a heavy object or assembling a desk. Unfortunately, applying IL to multi-arm manipulation tasks has ... |
Scalable Learning of Safety Guarantees for Autonomous Systems using Hamilton-Jacobi Reachability | https://ieeexplore.ieee.org/document/9561561/ | [
"Sylvia Herbert",
"Jason J. Choi",
"Suvansh Sanjeev",
"Marsalis Gibson",
"Koushil Sreenath",
"Claire J. Tomlin",
"Sylvia Herbert",
"Jason J. Choi",
"Suvansh Sanjeev",
"Marsalis Gibson",
"Koushil Sreenath",
"Claire J. Tomlin"
] | Autonomous systems like aircraft and assistive robots often operate in scenarios where guaranteeing safety is critical. Methods like Hamilton-Jacobi reachability can provide guaranteed safe sets and controllers for such systems. However, often these same scenarios have unknown or uncertain environments, system dynamics, or predictions of other agents. As the system is operating, it may learn new k... |
OmniHang: Learning to Hang Arbitrary Objects using Contact Point Correspondences and Neural Collision Estimation | https://ieeexplore.ieee.org/document/9560971/ | [
"Yifan You",
"Lin Shao",
"Toki Migimatsu",
"Jeannette Bohg",
"Yifan You",
"Lin Shao",
"Toki Migimatsu",
"Jeannette Bohg"
] | In this paper, we explore whether a robot can learn to hang arbitrary objects onto a diverse set of supporting items such as racks or hooks. Endowing robots with such an ability has applications in many domains such as domestic services, logistics, or manufacturing. Yet, it is a challenging manipulation task due to the large diversity of geometry and topology of everyday objects. In this paper, we... |
Asynchronous Multi-View SLAM | https://ieeexplore.ieee.org/document/9561481/ | [
"Anqi Joyce Yang",
"Can Cui",
"Ioan Andrei Bârsan",
"Raquel Urtasun",
"Shenlong Wang",
"Anqi Joyce Yang",
"Can Cui",
"Ioan Andrei Bârsan",
"Raquel Urtasun",
"Shenlong Wang"
] | Existing multi-camera SLAM systems assume synchronized shutters for all cameras, which is often not the case in practice. In this work, we propose a generalized multi-camera SLAM formulation which accounts for asynchronous sensor observations. Our framework integrates a continuous-time motion model to relate information across asynchronous multi-frames during tracking, local mapping, and loop clos... |
Fusion-DHL: WiFi, IMU, and Floorplan Fusion for Dense History of Locations in Indoor Environments | https://ieeexplore.ieee.org/document/9561115/ | [
"Sachini Herath",
"Saghar Irandoust",
"Bowen Chen",
"Yiming Qian",
"Pyojin Kim",
"Yasutaka Furukawa",
"Sachini Herath",
"Saghar Irandoust",
"Bowen Chen",
"Yiming Qian",
"Pyojin Kim",
"Yasutaka Furukawa"
] | The paper proposes a multi-modal sensor fusion algorithm that fuses WiFi, IMU, and floorplan information to infer an accurate and dense location history in indoor environments. The algorithm uses 1) an inertial navigation algorithm to estimate a relative motion trajectory from IMU sensor data; 2) a WiFi-based localization API in industry to obtain positional constraints and geo-localize the trajec... |
LVI-SAM: Tightly-coupled Lidar-Visual-Inertial Odometry via Smoothing and Mapping | https://ieeexplore.ieee.org/document/9561996/ | [
"Tixiao Shan",
"Brendan Englot",
"Carlo Ratti",
"Daniela Rus",
"Tixiao Shan",
"Brendan Englot",
"Carlo Ratti",
"Daniela Rus"
] | We propose a framework for tightly-coupled lidar-visual-inertial odometry via smoothing and mapping, LVI-SAM, that achieves real-time state estimation and map-building with high accuracy and robustness. LVI-SAM is built atop a factor graph and is composed of two sub-systems: a visual-inertial system (VIS) and a lidar-inertial system (LIS). The two sub-systems are designed in a tightly-coupled mann... |
Learned Uncertainty Calibration for Visual Inertial Localization | https://ieeexplore.ieee.org/document/9561179/ | [
"Stephanie Tsuei",
"Stefano Soatto",
"Paulo Tabuada",
"Mark B. Milam",
"Stephanie Tsuei",
"Stefano Soatto",
"Paulo Tabuada",
"Mark B. Milam"
] | The widely-used Extended Kalman Filter (EKF) provides a straightforward recipe to estimate the mean and covariance of the state given all past measurements in a causal and recursive fashion. For a wide variety of applications, the EKF is known to produce accurate estimates of the mean and typically inaccurate estimates of the covariance. For applications in visual inertial localization, we show th... |
Distributed Client-Server Optimization for SLAM with Limited On-Device Resources | https://ieeexplore.ieee.org/document/9561638/ | [
"Yetong Zhang",
"Ming Hsiao",
"Yipu Zhao",
"Jing Dong",
"Jakob J. Engel",
"Yetong Zhang",
"Ming Hsiao",
"Yipu Zhao",
"Jing Dong",
"Jakob J. Engel"
] | Simultaneous localization and mapping (SLAM) is a crucial functionality for exploration robots and virtual/augmented reality (VR/AR) devices. However, some of such devices with limited resources cannot afford the computational or memory cost to run full SLAM algorithms. We propose a general client-server SLAM optimization framework that achieves accurate real-time state estimation on the device wi... |
Model Predictive Control for Cooperative Hunting in Obstacle Rich and Dynamic Environments | https://ieeexplore.ieee.org/document/9561054/ | [
"Jacky Liao",
"Che Liu",
"Hugh H.T. Liu",
"Jacky Liao",
"Che Liu",
"Hugh H.T. Liu"
] | This paper studies the cooperative hunting problem, where a group of agents encircle a target while avoiding collisions with each other and with obstacles in the environment. The paper deals with obstacle rich environments and dynamic (moving obstacle) environments by formulating the problem as both a control problem and a planning problem. A model predictive control (MPC) method is proposed which... |
Instance-Aware Predictive Navigation in Multi-Agent Environments | https://ieeexplore.ieee.org/document/9561235/ | [
"Jinkun Cao",
"Xin Wang",
"Trevor Darrell",
"Fisher Yu",
"Jinkun Cao",
"Xin Wang",
"Trevor Darrell",
"Fisher Yu"
] | In this work, we aim to achieve efficient end-to-end learning of driving policies in dynamic multi-agent environments. Predicting and anticipating future events at the object level are critical for making informed driving decisions. We propose an Instance-Aware Predictive Control (IPC) approach, which forecasts interactions between agents as well as future scene structures. We adopt a novel multi-... |
SimNet: Learning Reactive Self-driving Simulations from Real-world Observations | https://ieeexplore.ieee.org/document/9561666/ | [
"Luca Bergamini",
"Yawei Ye",
"Oliver Scheel",
"Long Chen",
"Chih Hu",
"Luca Del Pero",
"Błażej Osiński",
"Hugo Grimmett",
"Peter Ondruska",
"Luca Bergamini",
"Yawei Ye",
"Oliver Scheel",
"Long Chen",
"Chih Hu",
"Luca Del Pero",
"Błażej Osiński",
"Hugo Grimmett",
"Peter Ondruska"
] | In this work we present a simple end-to-end trainable machine learning system capable of realistically simulating driving experiences. This can be used for verification of self-driving system performance without relying on expensive and time-consuming road testing. In particular, we frame the simulation problem as a Markov Process, leveraging deep neural networks to model both state distribution a... |
Robotic Information Gathering using Semantic Language Instructions | https://ieeexplore.ieee.org/document/9561317/ | [
"Ian C. Rankin",
"Seth McCammon",
"Geoffrey A. Hollinger",
"Ian C. Rankin",
"Seth McCammon",
"Geoffrey A. Hollinger"
] | This paper presents a framework that uses language instructions to define the constraints and objectives for robots gathering information about their environment. Designing autonomous robotic sampling missions requires deep knowledge of both autonomy systems and scientific domain expertise. Language commands provide an intuitive interface for operators to give complex instructions to robots. The k... |
Deep Structured Reactive Planning | https://ieeexplore.ieee.org/document/9561123/ | [
"Jerry Liu",
"Wenyuan Zeng",
"Raquel Urtasun",
"Ersin Yumer",
"Jerry Liu",
"Wenyuan Zeng",
"Raquel Urtasun",
"Ersin Yumer"
] | An intelligent agent operating in the real-world must balance achieving its goal with maintaining the safety and comfort of not only itself, but also other participants within the surrounding scene. This requires jointly reasoning about the behavior of other actors while deciding its own actions as these two processes are inherently intertwined – a vehicle will yield to us if we decide to proceed ... |
Learning a Centroidal Motion Planner for Legged Locomotion | https://ieeexplore.ieee.org/document/9562022/ | [
"Julian Viereck",
"Ludovic Righetti",
"Julian Viereck",
"Ludovic Righetti"
] | Whole-body optimizers have been successful at automatically computing complex dynamic locomotion behaviors. However they are often limited to offline planning as they are computationally too expensive to replan with a high frequency. Simpler models are then typically used for online replanning. In this paper we present a method to generate whole body movements in real-time for locomotion tasks. Ou... |
Optimizing Cellular Networks via Continuously Moving Base Stations on Road Networks | https://ieeexplore.ieee.org/document/9561052/ | [
"Yogesh Girdhar",
"Dmitriy Rivkin",
"Di Wu",
"Michael Jenkin",
"Xue Liu",
"Gregory Dudek",
"Yogesh Girdhar",
"Dmitriy Rivkin",
"Di Wu",
"Michael Jenkin",
"Xue Liu",
"Gregory Dudek"
] | Although existing cellular network base stations are typically immobile, the recent development of small form factor base stations and self driving cars has enabled the possibility of deploying a team of continuously moving base stations that can reorganize the network infrastructure to adapt to changing network traffic usage patterns. Given such a system of mobile base stations (MBSes) that can f... |
The Resh Programming Language for Multirobot Orchestration | https://ieeexplore.ieee.org/document/9561133/ | [
"Martin Carroll",
"Kedar S. Namjoshi",
"Itai Segall",
"Martin Carroll",
"Kedar S. Namjoshi",
"Itai Segall"
] | This paper describes Resh, a new, statically typed, interpreted programming language and associated runtime for orchestrating multirobot systems. The main features of Resh are: (1) It offloads much of the tedious work of programming such systems away from the programmer and into the language runtime; (2) It is based on a small set of temporal and locational operators; and (3) It is not restricted ... |
Sensing via Collisions: a Smart Cage for Quadrotors with Applications to Self-Localization | https://ieeexplore.ieee.org/document/9561896/ | [
"Cheng Liu",
"Roberto Tron",
"Cheng Liu",
"Roberto Tron"
] | Applications of micro unmanned aerial vehicles (UAVs) are gradually expanding into complex urban and natural environments. Despite noticeable progress, flying robots in obstacle-rich environments is still challenging. On-board processing for detecting and avoiding obstacles is possible, but at a significant computational expense, and with significant limitations (e.g., for obstacles with small cro... |
Generative Design of NU’s Husky Carbon, A Morpho-Functional, Legged Robot | https://ieeexplore.ieee.org/document/9561196/ | [
"Alireza Ramezani",
"Pravin Dangol",
"Eric Sihite",
"Andrew Lessieur",
"Peter Kelly",
"Alireza Ramezani",
"Pravin Dangol",
"Eric Sihite",
"Andrew Lessieur",
"Peter Kelly"
] | We report the design of a morpho-functional robot called Husky Carbon. Our goal is to integrate two forms of mobility, aerial and quadrupedal legged locomotion, within a single platform. There are prohibitive design restrictions such as tight power budget and payload, which can particularly become important in aerial flights. To address these challenges, we pose a problem called the Mobility Value... |
Learning Bipedal Robot Locomotion from Human Movement | https://ieeexplore.ieee.org/document/9561591/ | [
"Michael Taylor",
"Sergey Bashkirov",
"Javier Fernandez Rico",
"Ike Toriyama",
"Naoyuki Miyada",
"Hideki Yanagisawa",
"Kensaku Ishizuka",
"Michael Taylor",
"Sergey Bashkirov",
"Javier Fernandez Rico",
"Ike Toriyama",
"Naoyuki Miyada",
"Hideki Yanagisawa",
"Kensaku Ishizuka"
] | Teaching an anthropomorphic robot from human example offers the opportunity to impart humanlike qualities on its movement. In this work we present a reinforcement learning based method for teaching a real world bipedal robot to perform movements directly from human motion capture data. Our method seamlessly transitions from training in a simulation environment to executing on a physical robot with... |
Learning Task Space Actions for Bipedal Locomotion | https://ieeexplore.ieee.org/document/9561705/ | [
"Helei Duan",
"Jeremy Dao",
"Kevin Green",
"Taylor Apgar",
"Alan Fern",
"Jonathan Hurst",
"Helei Duan",
"Jeremy Dao",
"Kevin Green",
"Taylor Apgar",
"Alan Fern",
"Jonathan Hurst"
] | Recent work has demonstrated the success of reinforcement learning (RL) for training bipedal locomotion policies for real robots. This prior work, however, has focused on learning joint-coordination controllers based on an objective of following joint trajectories produced by already available controllers. As such, it is difficult to train these approaches to achieve higher-level goals of legged l... |
Preference-Based Learning for User-Guided HZD Gait Generation on Bipedal Walking Robots | https://ieeexplore.ieee.org/document/9561515/ | [
"Maegan Tucker",
"Noel Csomay-Shanklin",
"Wen-Loong Ma",
"Aaron D. Ames",
"Maegan Tucker",
"Noel Csomay-Shanklin",
"Wen-Loong Ma",
"Aaron D. Ames"
] | This paper presents a framework that leverages both control theory and machine learning to obtain stable and robust bipedal locomotion without the need for manual parameter tuning. Traditionally, gaits are generated through trajectory optimization methods and then realized experimentally — a process that often requires extensive tuning due to differences between the models and hardware. In this wo... |
Reinforcement Learning for Robust Parameterized Locomotion Control of Bipedal Robots | https://ieeexplore.ieee.org/document/9560769/ | [
"Zhongyu Li",
"Xuxin Cheng",
"Xue Bin Peng",
"Pieter Abbeel",
"Sergey Levine",
"Glen Berseth",
"Koushil Sreenath",
"Zhongyu Li",
"Xuxin Cheng",
"Xue Bin Peng",
"Pieter Abbeel",
"Sergey Levine",
"Glen Berseth",
"Koushil Sreenath"
] | Developing robust walking controllers for bipedal robots is a challenging endeavor. Traditional model-based locomotion controllers require simplifying assumptions and careful modelling; any small errors can result in unstable control. To address these challenges for bipedal locomotion, we present a model-free reinforcement learning framework for training robust locomotion policies in simulation, w... |
Online Dynamic Time Warping Algorithm for Human-Robot Imitation | https://ieeexplore.ieee.org/document/9562110/ | [
"Nazita Taghavi",
"Jacob Berdichevsky",
"Namrata Balakrishnan",
"Karla C. Welch",
"Sumit Kumar Das",
"Dan O. Popa",
"Nazita Taghavi",
"Jacob Berdichevsky",
"Namrata Balakrishnan",
"Karla C. Welch",
"Sumit Kumar Das",
"Dan O. Popa"
] | In this paper, we propose a novel online algorithm for motion similarity measurements during human-robot interaction (HRI). Specifically, we formulate a Segment-based Online Dynamic Time Warping (SODTW) algorithm that can be used for understanding of repeated and cyclic human motions, in the context of rehabilitation or social interaction. The algorithm can estimate both the human-robot motion sim... |
Investigation of Multiple Resource Theory Design Principles on Robot Teleoperation and Workload Management | https://ieeexplore.ieee.org/document/9561182/ | [
"Zhao Han",
"Adam Norton",
"Eric McCann",
"Lisa Baraniecki",
"Will Ober",
"Dave Shane",
"Anna Skinner",
"Holly A. Yanco",
"Zhao Han",
"Adam Norton",
"Eric McCann",
"Lisa Baraniecki",
"Will Ober",
"Dave Shane",
"Anna Skinner",
"Holly A. Yanco"
] | Robot interfaces often only use the visual channel. Inspired by Wickens’ Multiple Resource Theory, we investigated if the addition of audio elements would reduce cognitive workload and improve performance. Specifically, we designed a search and threat-defusal task (primary) with a memory test task (secondary). Eleven participants – predominantly first responders – were recruited to control a robot... |
Time-Domain Passivity-based Controller with an Optimal Two-channel Lawrence Telerobotic Architecture | https://ieeexplore.ieee.org/document/9561930/ | [
"Navid Feizi",
"Smrithi Thudi",
"Rajni V. Patel",
"S. Farokh Atashzar",
"Navid Feizi",
"Smrithi Thudi",
"Rajni V. Patel",
"S. Farokh Atashzar"
] | The time-domain passivity approach has been proposed in the literature in a variety of formats to guarantee the stability of teleoperation leader-follower systems. The conventional use of the proposed technique utilizes the control effort at the follower side as the force feedback to be sent back to the user at the leader’s side. However, this has resulted in transparency problems, especially when... |
Can Therapists Design Robot-Mediated Interventions and Teleoperate Robots Using VR to Deliver Interventions for ASD? | https://ieeexplore.ieee.org/document/9561112/ | [
"Roman Kulikovskiy",
"Megan Sochanski",
"Ala’aldin Hijaz",
"Matteson Eaton",
"Jessica Korneder",
"Wing-Yue Geoffrey Louie",
"Roman Kulikovskiy",
"Megan Sochanski",
"Ala’aldin Hijaz",
"Matteson Eaton",
"Jessica Korneder",
"Wing-Yue Geoffrey Louie"
] | Socially Assistive Robots (SARs) have demonstrated success in the delivery of interventions to individuals with Autism Spectrum Disorder (ASD). To date, these robot-mediated interventions have primarily been designed and implemented by robotics researchers. It remains unclear whether therapists could independently utilize robots to deliver therapies in clinical settings. In this paper, we conducte... |
A Low-cost Intrinsically Safe Mechanism for Physical Distancing Between Clinicians and Patients | https://ieeexplore.ieee.org/document/9561489/ | [
"Abed Soleymani",
"Ali Torabi",
"Mahdi Tavakoli",
"Abed Soleymani",
"Ali Torabi",
"Mahdi Tavakoli"
] | During the COVID-19 pandemic, due to the unprecedented workload and cross-infection hazard, the health-care workers’ lives are under a significant threat. However, minimizing the duration and frequency of close clinician-to-patient contacts using simple technologies that enable physical distancing could reduce the risk of spreading the disease. In this context, this paper presents the conceptual d... |
Collaborative Fall Detection using a Wearable Device and a Companion Robot | https://ieeexplore.ieee.org/document/9561323/ | [
"Fei Liang",
"Ricardo Hernandez",
"Jiaxing Lu",
"Brandon Ong",
"Matthew Jackson Moore",
"Weihua Sheng",
"Senlin Zhang",
"Fei Liang",
"Ricardo Hernandez",
"Jiaxing Lu",
"Brandon Ong",
"Matthew Jackson Moore",
"Weihua Sheng",
"Senlin Zhang"
] | Older adults who age in place face many health problems and need to be taken care of. Fall is a serious problem among elderly people. In this paper, we present the design and implementation of collaborative fall detection using a wearable device and a companion robot. First, we developed a wearable device by integrating a camera, an accelerometer and a microphone. Second, a companion robot communi... |
Intermittent Visual Servoing: Efficiently Learning Policies Robust to Instrument Changes for High-precision Surgical Manipulation | https://ieeexplore.ieee.org/document/9561070/ | [
"Samuel Paradis",
"Minho Hwang",
"Brijen Thananjeyan",
"Jeffrey Ichnowski",
"Daniel Seita",
"Danyal Fer",
"Thomas Low",
"Joseph E. Gonzalez",
"Ken Goldberg",
"Samuel Paradis",
"Minho Hwang",
"Brijen Thananjeyan",
"Jeffrey Ichnowski",
"Daniel Seita",
"Danyal Fer",
"Thomas Low",
"Joseph E. Gonzalez",
"Ken Goldberg"
] | Assisting surgeons with automation of surgical subtasks is challenging due to backlash, hysteresis, and variable tensioning in cable-driven robots. These issues are exacerbated as surgical instruments are changed during an operation. In this work, we propose a framework for automation of high- precision surgical subtasks by learning local, sample-efficient, accurate, closed-loop policies that use ... |
Crawling Support Using Wearable SuperLimbs: Human-Robot Synchronization and Metabolic Cost Assessment | https://ieeexplore.ieee.org/document/9561992/ | [
"Phillip Daniel",
"H. Harry Asada",
"Phillip Daniel",
"H. Harry Asada"
] | A pair of Supernumerary Robotic Limbs (Super-Limbs) can brace the wearer’s upper body while they work at floor level, and support them during crawling. The SuperLimbs’ motion is synchronized with the operator to mimic natural human crawling. This synchronization relies on experimental data from the operator’s observed crawl. A method for predicting the phase difference between the SuperLimbs’ hand... |
ROIAL: Region of Interest Active Learning for Characterizing Exoskeleton Gait Preference Landscapes | https://ieeexplore.ieee.org/document/9560840/ | [
"Kejun Li",
"Maegan Tucker",
"Erdem Bıyık",
"Ellen Novoseller",
"Joel W. Burdick",
"Yanan Sui",
"Dorsa Sadigh",
"Yisong Yue",
"Aaron D. Ames",
"Kejun Li",
"Maegan Tucker",
"Erdem Bıyık",
"Ellen Novoseller",
"Joel W. Burdick",
"Yanan Sui",
"Dorsa Sadigh",
"Yisong Yue",
"Aaron D. Ames"
] | Characterizing what types of exoskeleton gaits are comfortable for users, and understanding the science of walking more generally, require recovering a user’s utility landscape. Learning these landscapes is challenging, as walking trajectories are defined by numerous gait parameters, data collection from human trials is expensive, and user safety and comfort must be ensured. This work proposes the... |
Control of a Transfemoral Prosthesis on Sloped Terrain using Continuous and Nonlinear Impedance Parameters | https://ieeexplore.ieee.org/document/9560910/ | [
"Namita Anil Kumar",
"Woolim Hong",
"Pilwon Hur",
"Namita Anil Kumar",
"Woolim Hong",
"Pilwon Hur"
] | The design of impedance controllers for sloped walking with a transfemoral prosthesis is a complex control problem that generally results in numerous tuning parameters. This study proposes an easy-to-tune sloped walking control scheme. While the ankle is controlled using impedance control, the knee is controlled using a hybrid strategy of impedance control and trajectory tracking. This study deriv... |
Model-Dependent Prosthesis Control with Interaction Force Estimation | https://ieeexplore.ieee.org/document/9561250/ | [
"Rachel Gehlhar",
"Aaron D. Ames",
"Rachel Gehlhar",
"Aaron D. Ames"
] | Current lower-limb prosthesis control methods are primarily model-independent — lacking formal guarantees of stability, relying largely on heuristic tuning parameters for good performance, and neglecting use of the natural dynamics of the system. Model-dependence for prosthesis controllers is difficult to achieve due to the unknown human dynamics. We build upon previous work which synthesized prov... |
End-to-end grasping policies for human-in-the-loop robots via deep reinforcement learning | https://ieeexplore.ieee.org/document/9561937/ | [
"Mohammadreza Sharif",
"Deniz Erdogmus",
"Christopher Amato",
"Taskin Padir",
"Mohammadreza Sharif",
"Deniz Erdogmus",
"Christopher Amato",
"Taskin Padir"
] | State-of-the-art human-in-the-loop robot grasping is hugely suffered by Electromyography (EMG) inference robustness issues. As a workaround, researchers have been looking into integrating EMG with other signals, often in an ad hoc manner. In this paper, we are presenting a method for end-to-end training of a policy for human-in-the-loop robot grasping on real reaching trajectories. For this purpos... |
Situational Confidence Assistance for Lifelong Shared Autonomy | https://ieeexplore.ieee.org/document/9561839/ | [
"Matthew Zurek",
"Andreea Bobu",
"Daniel S. Brown",
"Anca D. Dragan",
"Matthew Zurek",
"Andreea Bobu",
"Daniel S. Brown",
"Anca D. Dragan"
] | Shared autonomy enables robots to infer user intent and assist in accomplishing it. But when the user wants to do a new task that the robot does not know about, shared autonomy will hinder their performance by attempting to assist them with something that is not their intent. Our key idea is that the robot can detect when its repertoire of intents is insufficient to explain the user's input, and g... |
Recognizing Orientation Slip in Human Demonstrations | https://ieeexplore.ieee.org/document/9561856/ | [
"Michael Hagenow",
"Bolun Zhang",
"Bilge Mutlu",
"Michael Zinn",
"Michael Gleicher",
"Michael Hagenow",
"Bolun Zhang",
"Bilge Mutlu",
"Michael Zinn",
"Michael Gleicher"
] | Manipulations of a constrained object often use a non-rigid grasp that allows the object to rotate relative to the end effector. This orientation slip strategy is often present in natural human demonstrations, yet it is generally overlooked in methods to identify constraints from such demonstrations. In this paper, we present a method to model and recognize prehensile orientation slip in human dem... |
Aggregating Long-Term Context for Learning Laparoscopic and Robot-Assisted Surgical Workflows | https://ieeexplore.ieee.org/document/9561770/ | [
"Yutong Ban",
"Guy Rosman",
"Thomas Ward",
"Daniel Hashimoto",
"Taisei Kondo",
"Hidekazu Iwaki",
"Ozanan Meireles",
"Daniela Rus",
"Yutong Ban",
"Guy Rosman",
"Thomas Ward",
"Daniel Hashimoto",
"Taisei Kondo",
"Hidekazu Iwaki",
"Ozanan Meireles",
"Daniela Rus"
] | Analyzing surgical workflow is crucial for surgical assistance robots to understand surgeries. With the understanding of the complete surgical workflow, the robots are able to assist the surgeons in intra-operative events, such as by giving a warning when the surgeon is entering specific keys or high-risk phases. Deep learning techniques have recently been widely applied to recognizing surgical wo... |
A Safe Hierarchical Planning Framework for Complex Driving Scenarios based on Reinforcement Learning | https://ieeexplore.ieee.org/document/9561195/ | [
"Jinning Li",
"Liting Sun",
"Jianyu Chen",
"Masayoshi Tomizuka",
"Wei Zhan",
"Jinning Li",
"Liting Sun",
"Jianyu Chen",
"Masayoshi Tomizuka",
"Wei Zhan"
] | Autonomous vehicles need to handle various traffic conditions and make safe and efficient decisions and maneuvers. However, on the one hand, a single optimization/sampling-based motion planner cannot efficiently generate safe trajectories in real time, particularly when there are many interactive vehicles near by. On the other hand, end-to-end learning methods cannot assure the safety of the outco... |
Behavior Planning at Urban Intersections through Hierarchical Reinforcement Learning | https://ieeexplore.ieee.org/document/9561095/ | [
"Zhiqian Qiao",
"Jeff Schneider",
"John M. Dolan",
"Zhiqian Qiao",
"Jeff Schneider",
"John M. Dolan"
] | For autonomous vehicles, effective behavior planning is crucial to ensure safety of the ego car. In many urban scenarios, it is hard to create sufficiently general heuristic rules, especially for challenging scenarios that some new human drivers find difficult. In this work, we propose a behavior planning structure based on reinforcement learning (RL) which is capable of performing autonomous vehi... |
Collision Avoidance in Tightly-Constrained Environments without Coordination: a Hierarchical Control Approach | https://ieeexplore.ieee.org/document/9561417/ | [
"Xu Shen",
"Edward L. Zhu",
"Yvonne R. Stürz",
"Francesco Borrelli",
"Xu Shen",
"Edward L. Zhu",
"Yvonne R. Stürz",
"Francesco Borrelli"
] | We present a hierarchical control approach for maneuvering an autonomous vehicle (AV) in tightly-constrained environments where other moving AVs and/or human driven vehicles are present. A two-level hierarchy is proposed: a high-level data-driven strategy predictor and a lower-level model-based feedback controller. The strategy predictor maps an encoding of a dynamic environment to a set of high-l... |
Zero-Potential-Energy Motions due to Stiffness in Impedance Control of Robotic Tasks: an Innovative Theory and Experimental Study | https://ieeexplore.ieee.org/document/9560809/ | [
"Carlos Saldarriaga",
"Imin Kao",
"Carlos Saldarriaga",
"Imin Kao"
] | This paper presents an analytical methodology and experimental study to identify quantitatively the zero-potential-energy (ZP) motion due to the stiffness matrices in Cartesian impedance control of redundant manipulators. This mode of motion, analogous to the rigid-body mode in classic mechanical systems, shows up as a result of the redundancy of the robot and creates a steady-state deviation from... |
No-frills Dynamic Planning using Static Planners | https://ieeexplore.ieee.org/document/9560762/ | [
"Mara Levy",
"Vasista Ayyagari",
"Abhinav Shrivastava",
"Mara Levy",
"Vasista Ayyagari",
"Abhinav Shrivastava"
] | In this paper, we address the task of interacting with dynamic environments where the changes in the environment are independent of the agent. We study this through the context of trapping a moving ball with a UR5 robotic arm. Our key contribution is an approach to utilize a static planner for dynamic tasks using a Dynamic Planning add-on; that is, if we can successfully solve a task with a static... |
PCMPC: Perception-Constrained Model Predictive Control for Quadrotors with Suspended Loads using a Single Camera and IMU | https://ieeexplore.ieee.org/document/9561449/ | [
"Guanrui Li",
"Alex Tunchez",
"Giuseppe Loianno",
"Guanrui Li",
"Alex Tunchez",
"Giuseppe Loianno"
] | In this paper, we address the Perception– Constrained Model Predictive Control (PCMPC) and state estimation problems for quadrotors with cable suspended payloads using a single camera and Inertial Measurement Unit (IMU). We design a receding–horizon control strategy for cable suspended payloads directly formulated on the system manifold configuration space SE (3) ×S2. The approach considers the sy... |
Learning Agile Locomotion Skills with a Mentor | https://ieeexplore.ieee.org/document/9561567/ | [
"Atil Iscen",
"George Yu",
"Alejandro Escontrela",
"Deepali Jain",
"Jie Tan",
"Ken Caluwaerts",
"Atil Iscen",
"George Yu",
"Alejandro Escontrela",
"Deepali Jain",
"Jie Tan",
"Ken Caluwaerts"
] | Developing agile behaviors for legged robots re-mains a challenging problem. While deep reinforcement learning is a promising approach, learning truly agile behaviors typically requires tedious reward shaping and careful curriculum design. We formulate agile locomotion as a multi-stage learning problem in which a mentor guides the agent throughout the training. The mentor is optimized to place a c... |
Automating Behavior Selection for Affective Telepresence Robot | https://ieeexplore.ieee.org/document/9560755/ | [
"Yurii Vasylkiv",
"Zhen Ma",
"Guangliang Li",
"Eleanor Sandry",
"Heike Brock",
"Keisuke Nakamura",
"Irani Pourang",
"Randy Gomez",
"Yurii Vasylkiv",
"Zhen Ma",
"Guangliang Li",
"Eleanor Sandry",
"Heike Brock",
"Keisuke Nakamura",
"Irani Pourang",
"Randy Gomez"
] | The tabletop robot Haru, used for affective telepresence research, enables a teleoperator to communicate affects from a distance. The robot’s expressiveness offers myriad ways of communicating affects through the execution of emotive routines. The teleoperator reacts to input modalities such as the user’s facial expression, gestures and speech-based intent as perceived by the robot’s perception sy... |
Fast Path Computation using Lattices in the Sensor-Space for Forest Navigation | https://ieeexplore.ieee.org/document/9561241/ | [
"Bernardo Martinez R. Junior",
"Guilherme A. S. Pereira",
"Bernardo Martinez R. Junior",
"Guilherme A. S. Pereira"
] | Fast autonomous motion in cluttered and unknown environments, such as forests, is highly dependent on low-latency obstacle avoidance strategies. In this context, this paper presents a motion planning strategy that relies on lattices for the fast computation of local paths that both avoid obstacles and follow a vector field that encodes the global robot task. Lattices are constructed in the sensor ... |
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