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Mass Estimation of a Moving Object Through Minimal Manipulation Interaction | https://ieeexplore.ieee.org/document/9560975/ | [
"Sergio Aguilera",
"Muhammad Ali Murtaza",
"Ye Zhao",
"Seth Hutchinson",
"Sergio Aguilera",
"Muhammad Ali Murtaza",
"Ye Zhao",
"Seth Hutchinson"
] | In this paper, we study the problem of dynamic interaction between a robot and an unknown object (e.g., catching a ball, or handing off an object during locomotion). In particular, we propose a method for estimating the inertial parameters of an object during dynamic interaction, while minimally altering the trajectory of the object – a minimal interaction approach. Our method combines trajectory ... |
GelSight Wedge: Measuring High-Resolution 3D Contact Geometry with a Compact Robot Finger | https://ieeexplore.ieee.org/document/9560783/ | [
"Shaoxiong Wang",
"Yu She",
"Branden Romero",
"Edward Adelson",
"Shaoxiong Wang",
"Yu She",
"Branden Romero",
"Edward Adelson"
] | Vision-based tactile sensors have the potential to provide important contact geometry to localize the objective with visual occlusion. However, it is challenging to measure high-resolution 3D contact geometry for a compact robot finger, to simultaneously meet optical and mechanical constraints. In this work, we present the GelSight Wedge sensor, which is optimized to have a compact shape for robot... |
Identifying External Contacts from Joint Torque Measurements on Serial Robotic Arms and Its Limitations | https://ieeexplore.ieee.org/document/9561761/ | [
"Tao Pang",
"Jack Umenberger",
"Russ Tedrake",
"Tao Pang",
"Jack Umenberger",
"Russ Tedrake"
] | The ability to detect and estimate external contacts is essential for robot arms to operate in unstructured environments occupied by humans. However, most robot arms are not equipped with adequate sensors to detect contacts on their entire body. What many robot arms do have is torque sensors for individual joints. Through a quantitative analysis, we argue that it is fairly likely for two distinct ... |
Contact Mode Guided Sampling-Based Planning for Quasistatic Dexterous Manipulation in 2D | https://ieeexplore.ieee.org/document/9560766/ | [
"Xianyi Cheng",
"Eric Huang",
"Yifan Hou",
"Matthew T. Mason",
"Xianyi Cheng",
"Eric Huang",
"Yifan Hou",
"Matthew T. Mason"
] | The discontinuities and multi-modality introduced by contacts make manipulation planning challenging. Many previous works avoid this problem by pre-designing a set of high-level motion primitives like grasping and pushing. However, such motion primitives are often not adequate to describe dexterous manipulation motions. In this work, we propose a method for dexterous manipulation planning at a mor... |
kPAM-SC: Generalizable Manipulation Planning using KeyPoint Affordance and Shape Completion | https://ieeexplore.ieee.org/document/9561428/ | [
"Wei Gao",
"Russ Tedrake",
"Wei Gao",
"Russ Tedrake"
] | While traditional approaches to manipulation planning assume known object templates, recent approaches to "category-level manipulation" aim to manipulate a category of objects with potentially unknown instances and large intra-category shape variation. In this paper we explore an object representation to enable precise category-level manipulation, capturing a notion of the object configuration and... |
Alternative Paths Planner (APP) for Provably Fixed-time Manipulation Planning in Semi-structured Environments | https://ieeexplore.ieee.org/document/9561563/ | [
"Fahad Islam",
"Chris Paxton",
"Clemens Eppner",
"Bryan Peele",
"Maxim Likhachev",
"Dieter Fox",
"Fahad Islam",
"Chris Paxton",
"Clemens Eppner",
"Bryan Peele",
"Maxim Likhachev",
"Dieter Fox"
] | In many applications, including logistics and manufacturing, robot manipulators operate in semi-structured environments alongside humans or other robots. These environments are largely static, but they may contain some movable obstacles that the robot must avoid. Manipulation tasks in these applications are often highly repetitive, but require fast and reliable motion planning capabilities, often ... |
Hierarchical Planning for Long-Horizon Manipulation with Geometric and Symbolic Scene Graphs | https://ieeexplore.ieee.org/document/9561548/ | [
"Yifeng Zhu",
"Jonathan Tremblay",
"Stan Birchfield",
"Yuke Zhu",
"Yifeng Zhu",
"Jonathan Tremblay",
"Stan Birchfield",
"Yuke Zhu"
] | We present a visually grounded hierarchical planning algorithm for long-horizon manipulation tasks. Our algorithm offers a joint framework of neuro-symbolic task planning and low-level motion generation conditioned on the specified goal. At the core of our approach is a two-level scene graph representation, namely geometric scene graph and symbolic scene graph. This hierarchical representation ser... |
Contact Localization for Robot Arms in Motion without Torque Sensing | https://ieeexplore.ieee.org/document/9562058/ | [
"Jacky Liang",
"Oliver Kroemer",
"Jacky Liang",
"Oliver Kroemer"
] | Detecting and localizing contacts is essential for robot manipulators to perform contact-rich tasks in unstructured environments. While robot skins can localize contacts on the surface of robot arms, these sensors are not yet robust or easily accessible. As such, prior works have explored using proprioceptive observations, such as joint velocities and torques, to perform contact localization. Many... |
Semi-Infinite Programming with Complementarity Constraints for Pose Optimization with Pervasive Contact | https://ieeexplore.ieee.org/document/9561609/ | [
"Mengchao Zhang",
"Kris Hauser",
"Mengchao Zhang",
"Kris Hauser"
] | This paper presents a novel computational model to address the problem that contact is an infinite phenomena involving continuous regions of interaction. The problem is cast as a semi-infinite program with complementarity constraints (SIPCC). Rather than pre-discretize contacting surfaces into a finite number of contact points, we use semi-infinite programming (SIP) techniques that operate on the ... |
Finite-Horizon Synthesis for Probabilistic Manipulation Domains | https://ieeexplore.ieee.org/document/9561297/ | [
"M. Wells",
"Zachary Kingston",
"Morteza Lahijanian",
"Lydia E. Kavraki",
"Moshe Y. Vardi",
"M. Wells",
"Zachary Kingston",
"Morteza Lahijanian",
"Lydia E. Kavraki",
"Moshe Y. Vardi"
] | Robots have begun operating and collaborating with humans in industrial and social settings. This collaboration introduces challenges: the robot must plan while taking the human’s actions into account. In prior work, the problem was posed as a 2-player deterministic game, with a limited number of human moves. The limit on human moves is unintuitive, and in many settings determinism is undesirable.... |
IKEA Furniture Assembly Environment for Long-Horizon Complex Manipulation Tasks | https://ieeexplore.ieee.org/document/9560986/ | [
"Youngwoon Lee",
"Edward S. Hu",
"Joseph J. Lim",
"Youngwoon Lee",
"Edward S. Hu",
"Joseph J. Lim"
] | The IKEA Furniture Assembly Environment is one of the first benchmarks for testing and accelerating the automation of long-horizon and hierarchical manipulation tasks. The environment is designed to advance reinforcement learning and imitation learning from simple toy tasks to complex tasks requiring both long-term planning and sophisticated low-level control. Our environment features 60 furniture... |
Learning Dexterous Grasping with Object-Centric Visual Affordances | https://ieeexplore.ieee.org/document/9561802/ | [
"Priyanka Mandikal",
"Kristen Grauman",
"Priyanka Mandikal",
"Kristen Grauman"
] | Dexterous robotic hands are appealing for their agility and human-like morphology, yet their high degree of freedom makes learning to manipulate challenging. We introduce an approach for learning dexterous grasping. Our key idea is to embed an object-centric visual affordance model within a deep reinforcement learning loop to learn grasping policies that favor the same object regions favored by pe... |
Learning Collaborative Pushing and Grasping Policies in Dense Clutter | https://ieeexplore.ieee.org/document/9561828/ | [
"Bingjie Tang",
"Matthew Corsaro",
"George Konidaris",
"Stefanos Nikolaidis",
"Stefanie Tellex",
"Bingjie Tang",
"Matthew Corsaro",
"George Konidaris",
"Stefanos Nikolaidis",
"Stefanie Tellex"
] | Robots must reason about pushing and grasping in order to engage in flexible manipulation in cluttered environments. Earlier works on learning pushing and grasping only consider each operation in isolation or are limited to top-down grasping and bin-picking. We train a robot to learn joint planar pushing and 6-degree-of-freedom (6-DoF) grasping policies by self-supervision. Two separate deep neura... |
Grasping with Chopsticks: Combating Covariate Shift in Model-free Imitation Learning for Fine Manipulation | https://ieeexplore.ieee.org/document/9561662/ | [
"Liyiming Ke",
"Jingqiang Wang",
"Tapomayukh Bhattacharjee",
"Byron Boots",
"Siddhartha Srinivasa",
"Liyiming Ke",
"Jingqiang Wang",
"Tapomayukh Bhattacharjee",
"Byron Boots",
"Siddhartha Srinivasa"
] | Billions of people use chopsticks, a simple yet versatile tool, for fine manipulation of everyday objects. The small, curved, and slippery tips of chopsticks pose a challenge for picking up small objects, making them a suitably complex test case. This paper leverages human demonstrations to develop an autonomous chopsticks-equipped robotic manipulator. Due to the lack of accurate models for fine m... |
Learning Task-Oriented Dexterous Grasping from Human Knowledge | https://ieeexplore.ieee.org/document/9562073/ | [
"Hui Li",
"Yinlong Zhang",
"Yanan Li",
"Hongsheng He",
"Hui Li",
"Yinlong Zhang",
"Yanan Li",
"Hongsheng He"
] | Industrial automation requires robot dexterity to automate many processes such as product assembling, packaging, and material handling. The existing robotic systems lack the capability to determining proper grasp strategies in the context of object affordances and task designations. In this paper, a framework of task-oriented dexterous grasping is proposed to learn grasp knowledge from human exper... |
Feedback Linearization for Quadrotors with a Learned Acceleration Error Model | https://ieeexplore.ieee.org/document/9561708/ | [
"Alexander Spitzer",
"Nathan Michael",
"Alexander Spitzer",
"Nathan Michael"
] | This paper enhances the feedback linearization controller for multirotors with a learned acceleration error model and a thrust input delay mitigation model. Feedback linearization controllers are theoretically appealing but their performance suffers on real systems, where the true system does not match the known system model. We take a step in reducing these robustness issues by learning an accele... |
Cirrus: A Long-range Bi-pattern LiDAR Dataset | https://ieeexplore.ieee.org/document/9561267/ | [
"Ze Wang",
"Sihao Ding",
"Ying Li",
"Jonas Fenn",
"Sohini Roychowdhury",
"Andreas Wallin",
"Lane Martin",
"Scott Ryvola",
"Guillermo Sapiro",
"Qiang Qiu",
"Ze Wang",
"Sihao Ding",
"Ying Li",
"Jonas Fenn",
"Sohini Roychowdhury",
"Andreas Wallin",
"Lane Martin",
"Scott Ryvola",
"Guillermo Sapiro",
"Qiang Qiu"
] | In this paper, we introduce Cirrus, a new long-range bi-pattern LiDAR public dataset for autonomous driving tasks such as 3D object detection, critical to highway driving and timely decision making. Our platform is equipped with a high-resolution video camera and a pair of LiDAR sensors with a 250-meter effective range, which is significantly longer than existing public datasets. We record paired ... |
Airflow-Inertial Odometry for Resilient State Estimation on Multirotors | https://ieeexplore.ieee.org/document/9561907/ | [
"Andrea Tagliabue",
"Jonathan P. How",
"Andrea Tagliabue",
"Jonathan P. How"
] | We present a dead reckoning strategy for increased resilience to position estimation failures on multirotors, using only data from a low-cost IMU and novel, bio-inspired airflow sensors. The goal is challenging, since low-cost IMUs are subject to large noise and drift, while 3D airflow sensing is made difficult by the interference caused by the propellers and by the wind. Our approach relies on a ... |
π-LSAM: LiDAR Smoothing and Mapping With Planes | https://ieeexplore.ieee.org/document/9561933/ | [
"Lipu Zhou",
"Shengze Wang",
"Michael Kaess",
"Lipu Zhou",
"Shengze Wang",
"Michael Kaess"
] | This paper introduces a real-time dense planar LiDAR SLAM system, named π-LSAM, for the indoor environment. The widely used LiDAR odometry and mapping (LOAM) framework [1] does not include bundle adjustment (BA) and generates a low fidelity tracking pose. This paper seeks to overcome these drawbacks for the indoor environment. Specifically, we use the plane as the landmark, and introduce plane adj... |
Robust Place Recognition using an Imaging Lidar | https://ieeexplore.ieee.org/document/9562105/ | [
"Tixiao Shan",
"Brendan Englot",
"Fábio Duarte",
"Carlo Ratti",
"Daniela Rus",
"Tixiao Shan",
"Brendan Englot",
"Fábio Duarte",
"Carlo Ratti",
"Daniela Rus"
] | We propose a methodology for robust, real-time place recognition using an imaging lidar, which yields image-quality high-resolution 3D point clouds. Utilizing the intensity readings of an imaging lidar, we project the point cloud and obtain an intensity image. ORB feature descriptors are extracted from the image and encoded into a bag-of-words vector. The vector, used to identify the point cloud, ... |
High-Speed Robot Navigation using Predicted Occupancy Maps | https://ieeexplore.ieee.org/document/9561034/ | [
"Kapil D. Katyal",
"Adam Polevoy",
"Joseph Moore",
"Craig Knuth",
"Katie M. Popek",
"Kapil D. Katyal",
"Adam Polevoy",
"Joseph Moore",
"Craig Knuth",
"Katie M. Popek"
] | Safe and high-speed navigation is a key enabling capability for real world deployment of robotic systems. A significant limitation of existing approaches is the computational bottleneck associated with explicit mapping and the limited field of view (FOV) of existing sensor technologies. In this paper, we study algorithmic approaches that allow the robot to predict spaces extending beyond the senso... |
The Fluid Field SLIP Model: Terrestrial-Aquatic Dynamic Legged Locomotion | https://ieeexplore.ieee.org/document/9561102/ | [
"Max P. Austin",
"Jonathan E. Clark",
"Max P. Austin",
"Jonathan E. Clark"
] | This paper describes the development of a single reduced-order dynamic model that captures running on land, running while submerged, and for the first time swimming on the surface of water. By capturing the effect of fluid forces on both the body and the leg, the Spring-Loaded Inverted Pendulum (SLIP) model is extended to operate in amphibious and aquatic regimes. Three distinct stable motion patt... |
Dynamics Randomization Revisited: A Case Study for Quadrupedal Locomotion | https://ieeexplore.ieee.org/document/9560837/ | [
"Zhaoming Xie",
"Xingye Da",
"Michiel van de Panne",
"Buck Babich",
"Animesh Garg",
"Zhaoming Xie",
"Xingye Da",
"Michiel van de Panne",
"Buck Babich",
"Animesh Garg"
] | Understanding the gap between simulation and reality is critical for reinforcement learning with legged robots, which are largely trained in simulation. However, recent work has resulted in sometimes conflicting conclusions with regard to which factors are important for success, including the role of dynamics randomization. In this paper, we aim to provide clarity and understanding on the role of ... |
Learning Multimodal Contact-Rich Skills from Demonstrations Without Reward Engineering | https://ieeexplore.ieee.org/document/9561734/ | [
"Mythra V. Balakuntala",
"Upinder Kaur",
"Xin Ma",
"Juan Wachs",
"Richard M. Voyles",
"Mythra V. Balakuntala",
"Upinder Kaur",
"Xin Ma",
"Juan Wachs",
"Richard M. Voyles"
] | Everyday contact-rich tasks, such as peeling, cleaning, and writing, demand multimodal perception for effective and precise task execution. However, these present a novel challenge to robots as they lack the ability to combine these multimodal stimuli for performing contact-rich tasks. Learning-based methods have attempted to model multi-modal contact-rich tasks, but they often require extensive t... |
DIPN: Deep Interaction Prediction Network with Application to Clutter Removal | https://ieeexplore.ieee.org/document/9561073/ | [
"Baichuan Huang",
"Shuai D. Han",
"Abdeslam Boularias",
"Jingjin Yu",
"Baichuan Huang",
"Shuai D. Han",
"Abdeslam Boularias",
"Jingjin Yu"
] | We propose a Deep Interaction Prediction Network (DIPN) for learning to predict complex interactions that ensue as a robot end-effector pushes multiple objects, whose physical properties, including size, shape, mass, and friction coefficients may be unknown a priori. DIPN "imagines" the effect of a push action and generates an accurate synthetic image of the predicted outcome. DIPN is shown to be ... |
Learning Sampling Distributions Using Local 3D Workspace Decompositions for Motion Planning in High Dimensions | https://ieeexplore.ieee.org/document/9561104/ | [
"Constantinos Chamzas",
"Zachary Kingston",
"Carlos Quintero-Peña",
"Anshumali Shrivastava",
"Lydia E. Kavraki",
"Constantinos Chamzas",
"Zachary Kingston",
"Carlos Quintero-Peña",
"Anshumali Shrivastava",
"Lydia E. Kavraki"
] | Earlier work has shown that reusing experience from prior motion planning problems can improve the efficiency of similar, future motion planning queries. However, for robots with many degrees-of-freedom, these methods exhibit poor generalization across different environments and often require large datasets that are impractical to gather. We present SPARK and FLAME, two experience-based frameworks... |
Learning and Planning for Temporally Extended Tasks in Unknown Environments | https://ieeexplore.ieee.org/document/9561819/ | [
"Christopher Bradley",
"Adam Pacheck",
"Gregory J. Stein",
"Sebastian Castro",
"Hadas Kress-Gazit",
"Nicholas Roy",
"Christopher Bradley",
"Adam Pacheck",
"Gregory J. Stein",
"Sebastian Castro",
"Hadas Kress-Gazit",
"Nicholas Roy"
] | We propose a novel planning technique for satisfying tasks specified in temporal logic in partially revealed environments. We define high-level actions derived from the environment and the given task itself, and estimate how each action contributes to progress towards completing the task. As the map is revealed, we estimate the cost and probability of success of each action from images and an enco... |
Behavior Tree Learning for Robotic Task Planning through Monte Carlo DAG Search over a Formal Grammar | https://ieeexplore.ieee.org/document/9561027/ | [
"Emily Scheide",
"Graeme Best",
"Geoffrey A. Hollinger",
"Emily Scheide",
"Graeme Best",
"Geoffrey A. Hollinger"
] | We present an algorithm for learning behavior trees for robotic task planning, which alleviates the need for time-intensive or infeasible manual design of control architectures. Our method involves representing the search space of behavior trees as a formal grammar and searching over this grammar by means of a new generalization of Monte Carlo tree search (MCTS) for directed acyclic graphs (DAGs),... |
Improving Off-road Planning Techniques with Learned Costs from Physical Interactions | https://ieeexplore.ieee.org/document/9561881/ | [
"Matthew Sivaprakasam",
"Samuel Triest",
"Wenshan Wang",
"Peng Yin",
"Sebastian Scherer",
"Matthew Sivaprakasam",
"Samuel Triest",
"Wenshan Wang",
"Peng Yin",
"Sebastian Scherer"
] | Autonomous ground vehicles have improved greatly over the past decades, but they still have their limitations when it comes to off-road environments. There is still a need for planning techniques that effectively handle physical interactions between a vehicle and its surroundings. We present a method of modifying a standard path planning algorithm to address these problems by incorporating a learn... |
A Comparison Between Joint Space and Task Space Mappings for Dynamic Teleoperation of an Anthropomorphic Robotic Arm in Reaction Tests | https://ieeexplore.ieee.org/document/9561368/ | [
"Sunyu Wang",
"Kevin Murphy",
"Dillan Kenney",
"Joao Ramos",
"Sunyu Wang",
"Kevin Murphy",
"Dillan Kenney",
"Joao Ramos"
] | Teleoperation—i.e., controlling a robot with human motion—proves promising in enabling a humanoid robot to move as dynamically as a human. But how to map human motion to a humanoid robot matters because a human and a humanoid robot rarely have identical topologies and dimensions. This work presents an experimental study that utilizes reaction tests to compare joint space and task space mappings fo... |
Identifying Driver Interactions via Conditional Behavior Prediction | https://ieeexplore.ieee.org/document/9561967/ | [
"Ekaterina Tolstaya",
"Reza Mahjourian",
"Carlton Downey",
"Balakrishnan Vadarajan",
"Benjamin Sapp",
"Dragomir Anguelov",
"Ekaterina Tolstaya",
"Reza Mahjourian",
"Carlton Downey",
"Balakrishnan Vadarajan",
"Benjamin Sapp",
"Dragomir Anguelov"
] | Interactive driving scenarios, such as lane changes, merges and unprotected turns, are some of the most challenging situations for autonomous driving. Planning in interactive scenarios requires accurately modeling the reactions of other agents to different future actions of the ego agent. We develop end-to-end models for conditional behavior prediction (CBP) that take as an input a query future tr... |
Autonomous Robotic Escort Incorporating Motion Prediction and Human Intention | https://ieeexplore.ieee.org/document/9561469/ | [
"Dean Conte",
"Tomonari Furukawa",
"Dean Conte",
"Tomonari Furukawa"
] | This paper presents a technique that allows a robot to escort a human to their destination. Unlike tracking where the robot follows the human from behind, the proposed technique locates the robot in front of the human by incorporating human intention in addition to conventional motion prediction. Human head pose is used as an effective past-proven implicit indicator of intention. A particle filter... |
Two-Stage Clustering of Human Preferences for Action Prediction in Assembly Tasks | https://ieeexplore.ieee.org/document/9561649/ | [
"Heramb Nemlekar",
"Jignesh Modi",
"Satyandra K. Gupta",
"Stefanos Nikolaidis",
"Heramb Nemlekar",
"Jignesh Modi",
"Satyandra K. Gupta",
"Stefanos Nikolaidis"
] | To effectively assist human workers in assembly tasks a robot must proactively offer support by inferring their preferences in sequencing the task actions. Previous work has focused on learning the dominant preferences of human workers for simple tasks largely based on their intended goal. However, people may have preferences at different resolutions: they may share the same high-level preference ... |
Dynamically Switching Human Prediction Models for Efficient Planning | https://ieeexplore.ieee.org/document/9561430/ | [
"Arjun Sripathy",
"Andreea Bobu",
"Daniel S. Brown",
"Anca D. Dragan",
"Arjun Sripathy",
"Andreea Bobu",
"Daniel S. Brown",
"Anca D. Dragan"
] | As environments involving both robots and humans become increasingly common, so does the need to account for people during planning. To plan effectively, robots must be able to respond to and sometimes influence what humans do. This requires a human model which predicts future human actions. A simple model may assume the human will continue what they did previously; a more complex one might predic... |
Temporal Anticipation and Adaptation Methods for Fluent Human-Robot Teaming | https://ieeexplore.ieee.org/document/9561763/ | [
"Tariq Iqbal",
"Laurel D. Riek",
"Tariq Iqbal",
"Laurel D. Riek"
] | As robots work with human teams, they will be expected to fluently coordinate with them. While people are adept at coordination and real-time adaptation, robots still lack this skill. In this paper, we introduce TANDEM: Temporal Anticipation and Adaptation for Machines, a series of neurobiologically-inspired algorithms that enable robots to fluently coordinate with people. TANDEM leverages a human... |
Robust Planning with Emergent Human-like Behavior for Agents Traveling in Groups | https://ieeexplore.ieee.org/document/9560989/ | [
"Shih-Yun Lo",
"Elaine Schaertl Short",
"Andrea L. Thomaz",
"Shih-Yun Lo",
"Elaine Schaertl Short",
"Andrea L. Thomaz"
] | To enable robots to smoothly interact with humans during their travels together as a group, robots need the ability to adapt their motions under environmental changes and ensure all group members’ routes are feasible. To achieve this ability, robots require knowledge of the final destination and the subgoals in between. In practice, such information is seldom shared explicitly among group members,... |
Order Matters: Generating Progressive Explanations for Planning Tasks in Human-Robot Teaming | https://ieeexplore.ieee.org/document/9561762/ | [
"Mehrdad Zakershahrak",
"Shashank Rao Marpally",
"Akshay Sharma",
"Ze Gong",
"Yu Zhang",
"Mehrdad Zakershahrak",
"Shashank Rao Marpally",
"Akshay Sharma",
"Ze Gong",
"Yu Zhang"
] | Prior work on generating explanations in a planning context has focused on providing the rationale behind an AI agent’s decision-making. While these methods offer the right explanations, they fail to heed the cognitive requirement of understanding an explanation from the explainee or human’s perspective. In this work, we set out to address this issue by considering the order for communicating info... |
Learning from Demonstration for Real-Time User Goal Prediction and Shared Assistive Control | https://ieeexplore.ieee.org/document/9560758/ | [
"Calvin Z. Qiao",
"Maram Sakr",
"Katharina Muelling",
"Henny Admoni",
"Calvin Z. Qiao",
"Maram Sakr",
"Katharina Muelling",
"Henny Admoni"
] | In shared autonomy, the user input is blended with the assistive motion to accomplish a task where the user goal is typically unknown to the robot. Transparency between the human and robot is essential for effective collaboration. Prior works have provided methods for the robot to infer the user goal; however, they are usually dependent on the distance between the robot and object, which may not b... |
Reaching Pruning Locations in a Vine Using a Deep Reinforcement Learning Policy | https://ieeexplore.ieee.org/document/9562075/ | [
"Francisco Yandun",
"Tanvir Parhar",
"Abhisesh Silwal",
"David Clifford",
"Zhiqiang Yuan",
"Gabriella Levine",
"Sergey Yaroshenko",
"George Kantor",
"Francisco Yandun",
"Tanvir Parhar",
"Abhisesh Silwal",
"David Clifford",
"Zhiqiang Yuan",
"Gabriella Levine",
"Sergey Yaroshenko",
"George Kantor"
] | We outline a neural network-based pipeline for perception, control and planning of a 7 DoF robot for tasks that involve reaching into a dormant grapevine canopy. The proposed system consists of a 6 DoF industrial robot arm and a linear slider that can actuate on an entire grape vine. Our approach uses Convolutional Neural Networks to detect buds in dormant grape vines and a Reinforcement Learning ... |
A Generative Model-Based Predictive Display for Robotic Teleoperation | https://ieeexplore.ieee.org/document/9561787/ | [
"Bowen Xie",
"Mingjie Han",
"Jun Jin",
"Martin Barczyk",
"Martin Jägersand",
"Bowen Xie",
"Mingjie Han",
"Jun Jin",
"Martin Barczyk",
"Martin Jägersand"
] | We propose a new generative model-based predictive display for robotic teleoperation over high-latency communication links. Our method is capable of rendering photo-realistic images of the scene to the human operator in real time from RGB-D images acquired by the remote robot. A preliminary exploration stage is used to build a coarse 3D map of the remote environment and to train a generative model... |
A Robot Walks into a Bar: Automatic Robot Joke Success Assessment | https://ieeexplore.ieee.org/document/9561941/ | [
"Ajitesh Srivastava",
"Naomi T. Fitter",
"Ajitesh Srivastava",
"Naomi T. Fitter"
] | Effective social robots should leverage humor’s unique ability to improve relationship connections and dispel stress, but current robots possess limited (if any) humorous abilities. In this paper, we aim to supplement one aspect of autonomous robots by giving robotic systems the ability to "read the room" to assess how their humorous statements are received by nearby people in real time. Using a d... |
Detecting and Counting Oysters | https://ieeexplore.ieee.org/document/9561268/ | [
"Behzad Sadrfaridpour",
"Yiannis Aloimonos",
"Miao Yu",
"Yang Tao",
"Donald Webster",
"Behzad Sadrfaridpour",
"Yiannis Aloimonos",
"Miao Yu",
"Yang Tao",
"Donald Webster"
] | Oysters are an essential species in the Chesapeake Bay living ecosystem. Oysters are filter feeders and considered the vacuum cleaners of the Chesapeake Bay that can considerably improve the Bay's water quality. Many oyster restoration programs have been initiated in the past decades and continued to date. Advancements in robotics and artificial intelligence have opened new opportunities for aquac... |
Autonomous Distributed 3D Radiation Field Estimation for Nuclear Environment Characterization | https://ieeexplore.ieee.org/document/9561922/ | [
"Frank Mascarich",
"Paolo De Petris",
"Huan Nguyen",
"Nikhil Khedekar",
"Kostas Alexis",
"Frank Mascarich",
"Paolo De Petris",
"Huan Nguyen",
"Nikhil Khedekar",
"Kostas Alexis"
] | This paper contributes a method designed to enable autonomous distributed 3D nuclear radiation field mapping. The algorithm uses a single radiation sensor and a sequence of spatially distributed and robotically acquired radiation measurements across a discretized 3D grid to derive a radiation gradient. The derived gradient is probabilistically propagated to unknown components of the map to further... |
Locomotion and Control of a Friction-Driven Tripedal Robot | https://ieeexplore.ieee.org/document/9561184/ | [
"Mark Hermes",
"Taylor McLaughlin",
"Mitul Luhar",
"Quan Nguyen",
"Mark Hermes",
"Taylor McLaughlin",
"Mitul Luhar",
"Quan Nguyen"
] | This paper presents a novel omnidirectional gait design and feedback control of a radially symmetric tripedal friction-driven robot. The robot features 3 servo motors mounted on a 3-D printed chassis 7 cm from the center of mass and separated 120 degrees. These motors drive limbs, which impart frictional reactive forces on the body. We first introduce a mathematical model for the robot motion, the... |
Design Considerations for a Steerable Needle Robot to Maximize Reachable Lung Volume | https://ieeexplore.ieee.org/document/9561342/ | [
"Inbar Fried",
"Janine Hoelscher",
"Mengyu Fu",
"Maxwell Emerson",
"Tayfun Efe Ertop",
"Margaret Rox",
"Josephine Granna",
"Alan Kuntz",
"Jason A. Akulian",
"Robert J. Webster",
"Ron Alterovitz",
"Inbar Fried",
"Janine Hoelscher",
"Mengyu Fu",
"Maxwell Emerson",
"Tayfun Efe Ertop",
"Margaret Rox",
"Josephine Granna",
"Alan Kuntz",
"Jason A. Akulian",
"Robert J. Webster",
"Ron Alterovitz"
] | Steerable needles that are able to follow curvilinear trajectories and steer around anatomical obstacles are a promising solution for many interventional procedures. In the lung, these needles can be deployed from the tip of a conventional bronchoscope to reach lung lesions for diagnosis. The reach of such a device depends on several design parameters including the bronchoscope diameter, the angle... |
Nth Order Analytical Time Derivatives of Inverse Dynamics in Recursive and Closed Forms | https://ieeexplore.ieee.org/document/9561773/ | [
"Shivesh Kumar",
"Andreas Müller",
"Shivesh Kumar",
"Andreas Müller"
] | Derivatives of equations of motion describing the rigid body dynamics are becoming increasingly relevant for the robotics community and find many applications in design and control of robotic systems. Controlling robots, and multibody systems comprising elastic components in particular, not only requires smooth trajectories but also the time derivatives of the control forces/torques, hence of the ... |
Efficient Configuration Exploration in Inverse Dynamics Acquisition of Robotic Manipulators | https://ieeexplore.ieee.org/document/9561587/ | [
"Farshad Khadivar",
"Sthithparagya Gupta",
"Walid Amanhoud",
"Aude Billard",
"Farshad Khadivar",
"Sthithparagya Gupta",
"Walid Amanhoud",
"Aude Billard"
] | The inverse dynamics of a robotic manipulator is instrumental in precise robot control and manipulation. However, acquiring such a model is challenging, not only due to unmodelled non-linearities such as joint friction, but also from a machine learning perspective (e.g., input space dimension, amount of data needed). The accuracy of such models, regardless of the learning techniques, relies on pro... |
SelfDeco: Self-Supervised Monocular Depth Completion in Challenging Indoor Environments | https://ieeexplore.ieee.org/document/9560831/ | [
"Jaehoon Choi",
"Dongki Jung",
"Yonghan Lee",
"Deokhwa Kim",
"Dinesh Manocha",
"Donghwan Lee",
"Jaehoon Choi",
"Dongki Jung",
"Yonghan Lee",
"Deokhwa Kim",
"Dinesh Manocha",
"Donghwan Lee"
] | We present a novel algorithm for self-supervised monocular depth completion. Our approach is based on training a neural network that requires only sparse depth measurements and corresponding monocular video sequences without dense depth labels. Our self-supervised algorithm is designed for challenging indoor environments with textureless regions, glossy and transparent surfaces, moving people, lon... |
Detect, Reject, Correct: Crossmodal Compensation of Corrupted Sensors | https://ieeexplore.ieee.org/document/9561847/ | [
"Michelle A. Lee",
"Matthew Tan",
"Yuke Zhu",
"Jeannette Bohg",
"Michelle A. Lee",
"Matthew Tan",
"Yuke Zhu",
"Jeannette Bohg"
] | Using sensor data from multiple modalities presents an opportunity to encode redundant and complementary features that can be useful when one modality is corrupted or noisy. Humans do this everyday, relying on touch and proprioceptive feedback in visually-challenging environments. However, robots might not always know when their sensors are corrupted, as even broken sensors can return valid values... |
Advanced Sensing Development to Support Robot Accuracy Assessment and Improvement | https://ieeexplore.ieee.org/document/9561242/ | [
"Guixiu Qiao",
"Guixiu Qiao"
] | Robots can perform various types of automated movements in the workspace. In recent years, robot applications have been expanded to a much wider scope, including robot machining, robot assembly, robot 3D printing, robot inspection, etc. Many of these applications require robots to have higher absolute accuracy compared with conventional robot part handling and welding. The capability to assess a r... |
Robotic Grasping of Fully-Occluded Objects using RF Perception | https://ieeexplore.ieee.org/document/9560956/ | [
"Tara Boroushaki",
"Junshan Leng",
"Ian Clester",
"Alberto Rodriguez",
"Fadel Adib",
"Tara Boroushaki",
"Junshan Leng",
"Ian Clester",
"Alberto Rodriguez",
"Fadel Adib"
] | We present the design, implementation, and evaluation of RF-Grasp, a robotic system that can grasp fully-occluded objects in unknown and unstructured environments. Unlike prior systems that are constrained by the line-of-sight perception of vision and infrared sensors, RF-Grasp employs RF (Radio Frequency) perception to identify and locate target objects through occlusions, and perform efficient e... |
A Simulation-Based Grasp Planner for Enabling Robotic Grasping during Composite Sheet Layup | https://ieeexplore.ieee.org/document/9560939/ | [
"Omey M. Manyar",
"Jaineel Desai",
"Nimish Deogaonkar",
"Rex Jomy Joesph",
"Rishi Malhan",
"Zachary McNulty",
"Bohan Wang",
"Jernej Barbič",
"Satyandra K. Gupta",
"Omey M. Manyar",
"Jaineel Desai",
"Nimish Deogaonkar",
"Rex Jomy Joesph",
"Rishi Malhan",
"Zachary McNulty",
"Bohan Wang",
"Jernej Barbič",
"Satyandra K. Gupta"
] | Composites are increasingly becoming a material of choice in the aerospace and automotive industries. Currently, many composite parts are produced by manually laying up sheets on complex molds. Composite sheet layup requires executing two main tasks: (1) grasping a sheet and (2) draping it on the mold. Automating the layup process requires automation of these two tasks. This paper is focused on th... |
Collision-free vector field guidance and MPC for a fixed-wing UAV | https://ieeexplore.ieee.org/document/9560850/ | [
"Leonardo A. A. Pereira",
"Arthur H. D. Nunes",
"Adriano M. C. Rezende",
"Vinicius M. Gonçalves",
"Guilherme V. Raffo",
"Luciano C. A. Pimenta",
"Leonardo A. A. Pereira",
"Arthur H. D. Nunes",
"Adriano M. C. Rezende",
"Vinicius M. Gonçalves",
"Guilherme V. Raffo",
"Luciano C. A. Pimenta"
] | The present work focuses on the development of an efficient path controller to guide a fixed-wing UAV (Unmanned Aerial Vehicle) to follow a closed curve and avoid unknown dynamic obstacles. Our strategy is composed of two layers: a top level layer responsible for guidance and a lower level layer responsible for tracking the references given by the top level. To solve the guidance problem, we propo... |
Toward Impact-resilient Quadrotor Design, Collision Characterization and Recovery Control to Sustain Flight after Collisions | https://ieeexplore.ieee.org/document/9561089/ | [
"Zhichao Liu",
"Konstantinos Karydis",
"Zhichao Liu",
"Konstantinos Karydis"
] | Collision detection and recovery for aerial robots remain a challenge because of the limited space for sensors and local stability of the flight controller. We introduce a novel collision-resilient quadrotor that features a compliant arm design to enable free flight while allowing for one passive degree of freedom to absorb shocks. We further propose a novel collision detection and characterizatio... |
Soft Hybrid Aerial Vehicle via Bistable Mechanism | https://ieeexplore.ieee.org/document/9561434/ | [
"Xuan Li",
"Jessica McWilliams",
"Minchen Li",
"Cynthia Sung",
"Chenfanfu Jiang",
"Xuan Li",
"Jessica McWilliams",
"Minchen Li",
"Cynthia Sung",
"Chenfanfu Jiang"
] | Unmanned aerial vehicles have been demonstrated successfully in a variety of tasks, including surveying and sampling tasks over large areas. These vehicles can take many forms. Quadrotors’ agility and ability to hover makes them well suited for navigating potentially tight spaces, while fixed wing aircraft are capable of efficient flight over long distances. Hybrid aerial vehicles (HAVs) attempt t... |
H-ModQuad: Modular Multi-Rotors with 4, 5, and 6 Controllable DOF | https://ieeexplore.ieee.org/document/9561016/ | [
"Jiawei Xu",
"Diego S. D’Antonio",
"David Saldaña",
"Jiawei Xu",
"Diego S. D’Antonio",
"David Saldaña"
] | Traditional aerial vehicles are usually custom-designed for specific tasks. Although they offer an efficient solution, they are not always able to adapt to changes in the task specification, e.g., increasing the payload. This applies to quadrotors, having a maximum payload and only four controllable degrees of freedom, limiting their adaptability to the task’s variations. We propose a versatile mo... |
Robust Adaptive Synchronization of Interconnected Heterogeneous Quadrotors Transporting a Cable-Suspended Load | https://ieeexplore.ieee.org/document/9561513/ | [
"G. A. Cardona",
"M. Arevalo-Castiblanco",
"D. Tellez-Castro",
"J. Calderon",
"E. Mojica-Nava",
"G. A. Cardona",
"M. Arevalo-Castiblanco",
"D. Tellez-Castro",
"J. Calderon",
"E. Mojica-Nava"
] | We tackle the problem of multiple quadrotors transporting a cable-suspended point-mass load. The quadrotors are treated as a virtual leader-follower algorithm, where a multi-layer graph encapsulates the communication and physical interaction. On the one hand, the communication stands for the approach of following the reference trajectory of a virtual leader. On the other hand, the load exerts a di... |
Adaptive Failure Search Using Critical States from Domain Experts | https://ieeexplore.ieee.org/document/9561477/ | [
"Peter Du",
"Katherine Driggs-Campbell",
"Peter Du",
"Katherine Driggs-Campbell"
] | Uncovering potential failure cases is a crucial step in the validation of safety critical systems such as autonomous vehicles. Failure search may be done through logging substantial vehicle miles in either simulation or real world testing. Due to the sparsity of failure events, naive random search approaches require significant amounts of vehicle operation hours to find potential system weaknesses... |
Policy Transfer via Kinematic Domain Randomization and Adaptation | https://ieeexplore.ieee.org/document/9561982/ | [
"Ioannis Exarchos",
"Yifeng Jiang",
"Wenhao Yu",
"C. Karen Liu",
"Ioannis Exarchos",
"Yifeng Jiang",
"Wenhao Yu",
"C. Karen Liu"
] | Transferring reinforcement learning policies trained in physics simulation to the real hardware remains a challenge, known as the "sim-to-real" gap. Domain randomization is a simple yet effective technique to address dynamics discrepancies across source and target domains, but its success generally depends on heuristics and trial-and-error. In this work we investigate the impact of randomized para... |
Uniform Complete Observability of Mass and Rotational Inertial Parameters in Adaptive Identification of Rigid-Body Plant Dynamics | https://ieeexplore.ieee.org/document/9561892/ | [
"Tyler M. Paine",
"Louis L. Whitcomb",
"Tyler M. Paine",
"Louis L. Whitcomb"
] | This paper addresses the long-standing open problem of observability of mass and inertia plant parameters in the adaptive identification (AID) of second-order nonlinear models of 6 degree-of-freedom rigid-body dynamical systems subject to externally applied forces and moments. Although stable methods for AID of plant parameters for this class of systems, as well numerous approaches to stable model... |
Assumption Monitoring Using Runtime Verification for UAV Temporal Task Plan Executions | https://ieeexplore.ieee.org/document/9561671/ | [
"Sebastián Zudaire",
"Felipe Gorostiaga",
"César Sánchez",
"Gerardo Schneider",
"Sebastián Uchitel",
"Sebastián Zudaire",
"Felipe Gorostiaga",
"César Sánchez",
"Gerardo Schneider",
"Sebastián Uchitel"
] | Temporal task planning guarantees a robot will succeed in its task as long as certain explicit and implicit assumptions about the robot’s operating environment, sensors, and capabilities hold. A robot executing a plan can silently fail to fulfill the task if the assumptions are violated at runtime. Monitoring assumption violations at runtime can flag silent failures and also provide mitigation and... |
Scalable POMDP Decision-Making Using Circulant Controllers | https://ieeexplore.ieee.org/document/9561478/ | [
"Kyle Hollins Wray",
"Kenneth Czuprynski",
"Kyle Hollins Wray",
"Kenneth Czuprynski"
] | This paper presents a novel policy representation for partially observable Markov decision processes (POMDPs) called circulant controllers and a provably efficient gradient-based algorithm for them. A formal mathematical description is provided that leverages circulant matrices for the controller’s stochastic node transitions. This structure is particularly effective for capturing decision-making ... |
Implicit Integration for Articulated Bodies with Contact via the Nonconvex Maximal Dissipation Principle | https://ieeexplore.ieee.org/document/9560924/ | [
"Zherong Pan",
"Kris Hauser",
"Zherong Pan",
"Kris Hauser"
] | We present non-convex maximal dissipation principle (NMDP), a time integration scheme for articulated bodies with simultaneous contacts. Our scheme resolves contact forces via the maximal dissipation principle (MDP). Whereas prior MDP solvers assume linearized dynamics and integrate using the forward multistep scheme, we consider the coupled system of nonlinear Newton-Euler dynamics and MDP and in... |
Shaping Rewards for Reinforcement Learning with Imperfect Demonstrations using Generative Models | https://ieeexplore.ieee.org/document/9561333/ | [
"Yuchen Wu",
"Melissa Mozifian",
"Florian Shkurti",
"Yuchen Wu",
"Melissa Mozifian",
"Florian Shkurti"
] | The potential benefits of model-free reinforcement learning to real robotics systems are limited by its uninformed exploration that leads to slow convergence, lack of data-efficiency, and unnecessary interactions with the environment. To address these drawbacks we propose a method that combines reinforcement and imitation learning by shaping the reward function with a state-and-action-dependent po... |
DisCo RL: Distribution-Conditioned Reinforcement Learning for General-Purpose Policies | https://ieeexplore.ieee.org/document/9561402/ | [
"Soroush Nasiriany",
"Vitchyr H. Pong",
"Ashvin Nair",
"Alexander Khazatsky",
"Glen Berseth",
"Sergey Levine",
"Soroush Nasiriany",
"Vitchyr H. Pong",
"Ashvin Nair",
"Alexander Khazatsky",
"Glen Berseth",
"Sergey Levine"
] | Can we use reinforcement learning to learn general-purpose policies that can perform a wide range of different tasks, resulting in flexible and reusable skills? Contextual policies provide this capability in principle, but the representation of the context determines the degree of generalization and expressivity. Categorical contexts preclude generalization to entirely new tasks. Goal-conditioned ... |
LASER: Learning a Latent Action Space for Efficient Reinforcement Learning | https://ieeexplore.ieee.org/document/9561232/ | [
"Arthur Allshire",
"Roberto Martín-Martín",
"Charles Lin",
"Shawn Manuel",
"Silvio Savarese",
"Animesh Garg",
"Arthur Allshire",
"Roberto Martín-Martín",
"Charles Lin",
"Shawn Manuel",
"Silvio Savarese",
"Animesh Garg"
] | The process of learning a manipulation task depends strongly on the action space used for exploration: posed in the incorrect action space, solving a task with reinforcement learning can be drastically inefficient. Additionally, similar tasks or instances of the same task family impose latent manifold constraints on the most effective action space: the task family can be best solved with actions i... |
Region-Based Planning for 3D Within-Hand-Manipulation via Variable Friction Robot Fingers and Extrinsic Contacts | https://ieeexplore.ieee.org/document/9561376/ | [
"Alp Sahin",
"Adam J. Spiers",
"Berk Calli",
"Alp Sahin",
"Adam J. Spiers",
"Berk Calli"
] | Attempts to achieve robotic Within-Hand-Manipulation (WIHM) generally utilize either high-DOF robotic hands with elaborate sensing apparatus or multi-arm robotic systems. In prior work we presented a simple robot hand with variable friction robot fingers, which allow a low-complexity approach to within-hand object translation and rotation, though this manipulation was limited to planar actions. In... |
Planning for Multi-stage Forceful Manipulation | https://ieeexplore.ieee.org/document/9561233/ | [
"Rachel Holladay",
"Tomás Lozano-Pérez",
"Alberto Rodriguez",
"Rachel Holladay",
"Tomás Lozano-Pérez",
"Alberto Rodriguez"
] | Multi-stage forceful manipulation tasks, such as twisting a nut on a bolt, require reasoning over interlocking constraints over discrete and continuous choices. The robot must choose a sequence of discrete actions, or strategy, such as whether to pick up an object, and the continuous parameters of each of those actions, such as how to grasp that object. In forceful manipulation tasks, the force re... |
Towards Robust Planar Translations using Delta-manipulator Arrays | https://ieeexplore.ieee.org/document/9561003/ | [
"Skye Thompson",
"Pragna Mannam",
"Zeynep Temel",
"Oliver Kroemer",
"Skye Thompson",
"Pragna Mannam",
"Zeynep Temel",
"Oliver Kroemer"
] | Distributed manipulators - consisting of a set of actuators or robots working cooperatively to achieve a manipulation task - are robust and flexible tools for performing a range of planar manipulation skills. One novel example is the delta array, a distributed manipulator composed of a grid of delta robots, capable of performing dexterous manipulation tasks using strategies incorporating both dyna... |
Manipulation Planning Among Movable Obstacles Using Physics-Based Adaptive Motion Primitives | https://ieeexplore.ieee.org/document/9561221/ | [
"Dhruv Mauria Saxena",
"Muhammad Suhail Saleem",
"Maxim Likhachev",
"Dhruv Mauria Saxena",
"Muhammad Suhail Saleem",
"Maxim Likhachev"
] | Robot manipulation in cluttered scenes often requires contact-rich interactions with objects. It can be more economical to interact via non-prehensile actions, for example, push through other objects to get to the desired grasp pose, instead of deliberate prehensile rearrangement of the scene. For each object in a scene, depending on its properties, the robot may or may not be allowed to make cont... |
Robotic Grasping through Combined Image-Based Grasp Proposal and 3D Reconstruction | https://ieeexplore.ieee.org/document/9562046/ | [
"Daniel Yang",
"Tarik Tosun",
"Benjamin Eisner",
"Volkan Isler",
"Daniel Lee",
"Daniel Yang",
"Tarik Tosun",
"Benjamin Eisner",
"Volkan Isler",
"Daniel Lee"
] | We present a novel approach to robotic grasp planning using both a learned grasp proposal network and a learned 3D shape reconstruction network. Our system generates 6-DOF grasps from a single RGB-D image of the target object, which is provided as input to both networks. By using the geometric reconstruction to refine the candidate grasp produced by the grasp proposal network, our system is able t... |
Attribute-Based Robotic Grasping with One-Grasp Adaptation | https://ieeexplore.ieee.org/document/9561139/ | [
"Yang Yang",
"Yuanhao Liu",
"Hengyue Liang",
"Xibai Lou",
"Changhyun Choi",
"Yang Yang",
"Yuanhao Liu",
"Hengyue Liang",
"Xibai Lou",
"Changhyun Choi"
] | Robotic grasping is one of the most fundamental robotic manipulation tasks and has been actively studied. However, how to quickly teach a robot to grasp a novel target object in clutter remains challenging. This paper attempts to tackle the challenge by leveraging object attributes that facilitate recognition, grasping, and quick adaptation. In this work, we introduce an end-to-end learning method... |
Collision-Aware Target-Driven Object Grasping in Constrained Environments | https://ieeexplore.ieee.org/document/9561473/ | [
"Xibai Lou",
"Yang Yang",
"Changhyun Choi",
"Xibai Lou",
"Yang Yang",
"Changhyun Choi"
] | Grasping a novel target object in constrained environments (e.g., walls, bins, and shelves) requires intensive reasoning about grasp pose reachability to avoid collisions with the surrounding structures. Typical 6-DoF robotic grasping systems rely on the prior knowledge about the environment and intensive planning computation, which is ungeneralizable and inefficient. In contrast, we propose a nov... |
6-DoF Contrastive Grasp Proposal Network | https://ieeexplore.ieee.org/document/9561954/ | [
"Xinghao Zhu",
"Lingfeng Sun",
"Yongxiang Fan",
"Masayoshi Tomizuka",
"Xinghao Zhu",
"Lingfeng Sun",
"Yongxiang Fan",
"Masayoshi Tomizuka"
] | Proposing grasp poses for novel objects is an essential component for any robot manipulation task. Planning six degrees of freedom (DoF) grasps with a single camera, however, is challenging due to the complex object shape, incomplete object information, and sensor noise. In this paper, we present a 6-DoF contrastive grasp proposal network (CGPN) to infer 6-DoF grasps from a single-view depth image... |
Decision Making in Joint Push-Grasp Action Space for Large-Scale Object Sorting | https://ieeexplore.ieee.org/document/9560782/ | [
"Zherong Pan",
"Kris Hauser",
"Zherong Pan",
"Kris Hauser"
] | We present a planner for large-scale (un)labeled object sorting tasks, which uses two types of manipulation actions: overhead grasping and planar pushing. The grasping action offers completeness guarantee under mild assumptions, and the planar pushing is an acceleration strategy that moves multiple objects at once. We make two main contributions: (1) We propose a bilevel planning algorithm. Our hi... |
Deep Affordance Foresight: Planning Through What Can Be Done in the Future | https://ieeexplore.ieee.org/document/9560841/ | [
"Danfei Xu",
"Ajay Mandlekar",
"Roberto Martín-Martín",
"Yuke Zhu",
"Silvio Savarese",
"Li Fei-Fei",
"Danfei Xu",
"Ajay Mandlekar",
"Roberto Martín-Martín",
"Yuke Zhu",
"Silvio Savarese",
"Li Fei-Fei"
] | Planning in realistic environments requires searching in large planning spaces. Affordances are a powerful concept to simplify this search, because they model what actions can be successful in a given situation. However, the classical notion of affordance is not suitable for long horizon planning because it only informs the robot about the immediate outcome of actions instead of what actions are b... |
Learning Dense Rewards for Contact-Rich Manipulation Tasks | https://ieeexplore.ieee.org/document/9561891/ | [
"Zheng Wu",
"Wenzhao Lian",
"Vaibhav Unhelkar",
"Masayoshi Tomizuka",
"Stefan Schaal",
"Zheng Wu",
"Wenzhao Lian",
"Vaibhav Unhelkar",
"Masayoshi Tomizuka",
"Stefan Schaal"
] | Rewards play a crucial role in reinforcement learning. To arrive at the desired policy, the design of a suitable reward function often requires significant domain expertise as well as trial-and-error. Here, we aim to minimize the effort involved in designing reward functions for contact-rich manipulation tasks. In particular, we provide an approach capable of extracting dense reward functions algo... |
ACRONYM: A Large-Scale Grasp Dataset Based on Simulation | https://ieeexplore.ieee.org/document/9560844/ | [
"Clemens Eppner",
"Arsalan Mousavian",
"Dieter Fox",
"Clemens Eppner",
"Arsalan Mousavian",
"Dieter Fox"
] | We introduce ACRONYM, a dataset for robot grasp planning based on physics simulation. The dataset contains 17.7M parallel-jaw grasps, spanning 8872 objects from 262 different categories, each labeled with the grasp result obtained from a physics simulator. We show the value of this large and diverse dataset by using it to train two state-of-the-art learning-based grasp planning algorithms. Grasp p... |
DWA-RL: Dynamically Feasible Deep Reinforcement Learning Policy for Robot Navigation among Mobile Obstacles | https://ieeexplore.ieee.org/document/9561462/ | [
"Utsav Patel",
"Nithish K Sanjeev Kumar",
"Adarsh Jagan Sathyamoorthy",
"Dinesh Manocha",
"Utsav Patel",
"Nithish K Sanjeev Kumar",
"Adarsh Jagan Sathyamoorthy",
"Dinesh Manocha"
] | We present a novel Deep Reinforcement Learning (DRL) based policy to compute dynamically feasible and spatially aware velocities for a robot navigating among mobile obstacles. Our approach combines the benefits of the Dynamic Window Approach (DWA) in terms of satisfying the robot’s dynamics constraints with state-of-the-art DRL-based navigation methods that can handle moving obstacles and pedestri... |
Reinforcement Learning for Autonomous Driving with Latent State Inference and Spatial-Temporal Relationships | https://ieeexplore.ieee.org/document/9562006/ | [
"Xiaobai Ma",
"Jiachen Li",
"Mykel J. Kochenderfer",
"David Isele",
"Kikuo Fujimura",
"Xiaobai Ma",
"Jiachen Li",
"Mykel J. Kochenderfer",
"David Isele",
"Kikuo Fujimura"
] | Deep reinforcement learning (DRL) provides a promising way for learning navigation in complex autonomous driving scenarios. However, identifying the subtle cues that can indicate drastically different outcomes remains an open problem with designing autonomous systems that operate in human environments. In this work, we show that explicitly inferring the latent state and encoding spatial-temporal r... |
Improving Ranging-Based Location Estimation with Rigidity-Constrained CRLB-Based Motion Planning | https://ieeexplore.ieee.org/document/9560750/ | [
"Justin Cano",
"Jerome Le Ny",
"Justin Cano",
"Jerome Le Ny"
] | Ranging systems can provide inexpensive, accurate, energy- and computationally-efficient navigation solutions for mobile robots. This work focuses on location and pose estimation in ranging networks composed of anchors with known positions as well as mobile robots modeled as rigid bodies, each carrying multiple tags to localize. Noisy distance measurements can be obtained between a subset of the n... |
Invariant Extended Kalman Filtering Using Two Position Receivers for Extended Pose Estimation | https://ieeexplore.ieee.org/document/9561150/ | [
"Natalia Pavlasek",
"Alex Walsh",
"James Richard Forbes",
"Natalia Pavlasek",
"Alex Walsh",
"James Richard Forbes"
] | This paper considers the use of two position receivers and an inertial measurement unit (IMU) to estimate the position, velocity, and attitude of a rigid body, collectively called extended pose. The measurement model consisting of the position of one receiver and the relative position between the two receivers is left invariant, enabling the use of the invariant extended Kalman filter (IEKF) frame... |
Compartmentalized Covariance Intersection: A Novel Filter Architecture for Distributed Localization | https://ieeexplore.ieee.org/document/9562080/ | [
"Adam Wiktor",
"Stephen Rock",
"Adam Wiktor",
"Stephen Rock"
] | This paper introduces the Compartmentalized Covariance Intersection (CCI) algorithm, a consistent technique to fuse measurements in cooperative navigation networks. The algorithm reduces the excess conservatism of standard Covariance Intersection (CI) by assuming that correlation is only present within each measurement stream and not across the different sources. This assumption allows the sources... |
3D Motion Capture of an Unmodified Drone with Single-chip Millimeter Wave Radar | https://ieeexplore.ieee.org/document/9561738/ | [
"Peijun Zhao",
"Chris Xiaoxuan Lu",
"Bing Wang",
"Niki Trigoni",
"Andrew Markham",
"Peijun Zhao",
"Chris Xiaoxuan Lu",
"Bing Wang",
"Niki Trigoni",
"Andrew Markham"
] | Accurate motion capture of aerial robots in 3D is a key enabler for autonomous operation in indoor environments such as warehouses or factories, as well as driving forward research in these areas. The most commonly used solutions at present are optical motion capture (e.g. VICON) and Ultrawide-band (UWB), but these are costly and cumbersome to deploy, due to their requirement of multiple cameras/a... |
Zero-Shot Reinforcement Learning on Graphs for Autonomous Exploration Under Uncertainty | https://ieeexplore.ieee.org/document/9561917/ | [
"Fanfei Chen",
"Paul Szenher",
"Yewei Huang",
"Jinkun Wang",
"Tixiao Shan",
"Shi Bai",
"Brendan Englot",
"Fanfei Chen",
"Paul Szenher",
"Yewei Huang",
"Jinkun Wang",
"Tixiao Shan",
"Shi Bai",
"Brendan Englot"
] | This paper studies the problem of autonomous exploration under localization uncertainty for a mobile robot with 3D range sensing. We present a framework for self-learning a high-performance exploration policy in a single simulation environment, and transferring it to other environments, which may be physical or virtual. Recent work in transfer learning achieves encouraging performance by domain ad... |
Fast Uncertainty Quantification for Deep Object Pose Estimation | https://ieeexplore.ieee.org/document/9561483/ | [
"Guanya Shi",
"Yifeng Zhu",
"Jonathan Tremblay",
"Stan Birchfield",
"Fabio Ramos",
"Animashree Anandkumar",
"Yuke Zhu",
"Guanya Shi",
"Yifeng Zhu",
"Jonathan Tremblay",
"Stan Birchfield",
"Fabio Ramos",
"Animashree Anandkumar",
"Yuke Zhu"
] | Deep learning-based object pose estimators are often unreliable and overconfident especially when the input image is outside the training domain, for instance, with sim2real transfer. Efficient and robust uncertainty quantification (UQ) in pose estimators is critically needed in many robotic tasks. In this work, we propose a simple, efficient, and plug-and-play UQ method for 6-DoF object pose esti... |
Mesh Reconstruction from Aerial Images for Outdoor Terrain Mapping Using Joint 2D-3D Learning | https://ieeexplore.ieee.org/document/9561337/ | [
"Qiaojun Feng",
"Nikolay Atanasov",
"Qiaojun Feng",
"Nikolay Atanasov"
] | This paper addresses outdoor terrain mapping using overhead images obtained from an unmanned aerial vehicle. Dense depth estimation from aerial images during flight is challenging. While feature-based localization and mapping techniques can deliver real-time odometry and sparse points reconstruction, a dense environment model is generally recovered offline with significant computation and storage.... |
ECNNs: Ensemble Learning Methods for Improving Planar Grasp Quality Estimation | https://ieeexplore.ieee.org/document/9561038/ | [
"Fadi Alladkani",
"James Akl",
"Berk Calli",
"Fadi Alladkani",
"James Akl",
"Berk Calli"
] | We present an ensemble learning methodology that combines multiple existing robotic grasp synthesis algorithms and obtain a success rate that is significantly better than the individual algorithms. The methodology treats the grasping algorithms as "experts" providing grasp "opinions". An Ensemble Convolutional Neural Network (ECNN) is trained using a Mixture of Experts (MOE) model that integrates ... |
Causal Reasoning in Simulation for Structure and Transfer Learning of Robot Manipulation Policies | https://ieeexplore.ieee.org/document/9561439/ | [
"Tabitha E. Lee",
"Jialiang Alan Zhao",
"Amrita S. Sawhney",
"Siddharth Girdhar",
"Oliver Kroemer",
"Tabitha E. Lee",
"Jialiang Alan Zhao",
"Amrita S. Sawhney",
"Siddharth Girdhar",
"Oliver Kroemer"
] | We present CREST, an approach for causal reasoning in simulation to learn the relevant state space for a robot manipulation policy. Our approach conducts interventions using internal models, which are simulations with approximate dynamics and simplified assumptions. These interventions elicit the structure between the state and action spaces, enabling construction of neural network policies with o... |
SuPer Deep: A Surgical Perception Framework for Robotic Tissue Manipulation using Deep Learning for Feature Extraction | https://ieeexplore.ieee.org/document/9561249/ | [
"Jingpei Lu",
"Ambareesh Jayakumari",
"Florian Richter",
"Yang Li",
"Michael C. Yip",
"Jingpei Lu",
"Ambareesh Jayakumari",
"Florian Richter",
"Yang Li",
"Michael C. Yip"
] | Robotic automation in surgery requires precise tracking of surgical tools and mapping of deformable tissue. Previous works on surgical perception frameworks require significant effort in developing features for surgical tool and tissue tracking. In this work, we overcome the challenge by exploiting deep learning methods for surgical perception. We integrated deep neural networks, capable of effici... |
Perceive, Attend, and Drive: Learning Spatial Attention for Safe Self-Driving | https://ieeexplore.ieee.org/document/9561904/ | [
"Bob Wei",
"Mengye Ren",
"Wenyuan Zeng",
"Ming Liang",
"Bin Yang",
"Raquel Urtasun",
"Bob Wei",
"Mengye Ren",
"Wenyuan Zeng",
"Ming Liang",
"Bin Yang",
"Raquel Urtasun"
] | In this paper, we propose an end-to-end self-driving network featuring a sparse attention module that learns to automatically attend to important regions of the input. The attention module specifically targets motion planning, whereas prior literature only applied attention in perception tasks. Learning an attention mask directly targeted for motion planning significantly improves the planner safe... |
Learning Human Objectives from Sequences of Physical Corrections | https://ieeexplore.ieee.org/document/9560829/ | [
"Mengxi Li",
"Alper Canberk",
"Dylan P. Losey",
"Dorsa Sadigh",
"Mengxi Li",
"Alper Canberk",
"Dylan P. Losey",
"Dorsa Sadigh"
] | When personal, assistive, and interactive robots make mistakes, humans naturally and intuitively correct those mistakes through physical interaction. In simple situations, one correction is sufficient to convey what the human wants. But when humans are working with multiple robots or the robot is performing an intricate task often the human must make several corrections to fix the robot’s behavior... |
SimGAN: Hybrid Simulator Identification for Domain Adaptation via Adversarial Reinforcement Learning | https://ieeexplore.ieee.org/document/9561731/ | [
"Yifeng Jiang",
"Tingnan Zhang",
"Daniel Ho",
"Yunfei Bai",
"C. Karen Liu",
"Sergey Levine",
"Jie Tan",
"Yifeng Jiang",
"Tingnan Zhang",
"Daniel Ho",
"Yunfei Bai",
"C. Karen Liu",
"Sergey Levine",
"Jie Tan"
] | As learning-based approaches progress towards automating robot controllers design, transferring learned policies to new domains with different dynamics (e.g. sim-to-real transfer) still demands manual effort. This paper introduces SimGAN, a framework to tackle domain adaptation by identifying a hybrid physics simulator to match the simulated trajectories to the ones from the target domain, using a... |
Look at my new blue force-sensing shoes! | https://ieeexplore.ieee.org/document/9562084/ | [
"Yuanfeng Han",
"Ruixin Li",
"Gregory S. Chirikjian",
"Yuanfeng Han",
"Ruixin Li",
"Gregory S. Chirikjian"
] | To function autonomously in the physical world, humanoid robots need high-fidelity sensing systems, especially for forces that cannot be easily modeled. Modeling forces in robot feet is particularly challenging due to static indeterminacy, thereby requiring direct sensing. Unfortunately, resolving forces in the feet of some smaller-sized humanoids is limited both by the quality of sensors and the ... |
UAV Target-Selection: 3D Pointing Interface System for Large-Scale Environment | https://ieeexplore.ieee.org/document/9561688/ | [
"Anna C. S. Medeiros",
"Photchara Ratsamee",
"Jason Orlosky",
"Yuki Uranishi",
"Manabu Higashida",
"Haruo Takemura",
"Anna C. S. Medeiros",
"Photchara Ratsamee",
"Jason Orlosky",
"Yuki Uranishi",
"Manabu Higashida",
"Haruo Takemura"
] | This paper presents a 3D pointing interface application to signal a UAV’s target in a large-scale environment. This system enables UAVs equipped with a monocular camera to determine which window of a building is selected by a human user in large-scale indoor or outdoor environments. The 3D pointing interface consists of three parts: YOLO, Open- Pose, and ORB-SLAM. YOLO detects the target objects, ... |
SQRP: Sensing Quality-aware Robot Programming System for Non-expert Programmers | https://ieeexplore.ieee.org/document/9561020/ | [
"Yi-Hsuan Hsieh",
"Pei-Chi Huang",
"Aloysius K Mok",
"Yi-Hsuan Hsieh",
"Pei-Chi Huang",
"Aloysius K Mok"
] | Robot programming typically makes use of a set of mechanical skills that is acquired by machine learning. Because there is in general no guarantee that machine learning produces robot programs that are free of surprising behavior, the safe execution of a robot program must utilize monitoring modules that take sensor data as inputs in real time to ensure the correctness of the skill execution. Owin... |
Automated Environment Reduction for Debugging Robotic Systems | https://ieeexplore.ieee.org/document/9561997/ | [
"Meriel von Stein",
"Sebastian Elbaum",
"Meriel von Stein",
"Sebastian Elbaum"
] | Complex environments can cause robots to fail. Identifying the key elements of the environment associated with such failures is critical for faster fault isolation and, ultimately, debugging those failures. In this work we present the first automated approach for reducing the environment in which a robot failed. Similar to software debugging techniques, our approach systematically performs a parti... |
ARROCH: Augmented Reality for Robots Collaborating with a Human | https://ieeexplore.ieee.org/document/9561144/ | [
"Kishan Chandan",
"Vidisha Kudalkar",
"Xiang Li",
"Shiqi Zhang",
"Kishan Chandan",
"Vidisha Kudalkar",
"Xiang Li",
"Shiqi Zhang"
] | Human-robot collaboration frequently requires extensive communication, e.g., using natural language and gesture. Augmented reality (AR) has provided an alternative way of bridging the communication gap between robots and people. However, most current AR-based human-robot communication methods are unidirectional, focusing on how the human adapts to robot behaviors, and are limited to single-robot d... |
ARC-LfD: Using Augmented Reality for Interactive Long-Term Robot Skill Maintenance via Constrained Learning from Demonstration | https://ieeexplore.ieee.org/document/9561844/ | [
"Matthew B. Luebbers",
"Connor Brooks",
"Carl L. Mueller",
"Daniel Szafir",
"Bradley Hayes",
"Matthew B. Luebbers",
"Connor Brooks",
"Carl L. Mueller",
"Daniel Szafir",
"Bradley Hayes"
] | Learning from Demonstration (LfD) enables novice users to teach robots new skills. However, many LfD methods do not facilitate skill maintenance and adaptation. Changes in task requirements or in the environment often reveal the lack of resiliency and adaptability in the skill model. To overcome these limitations, we introduce ARC-LfD: an Augmented Reality (AR) interface for constrained Learning f... |
Bringing WALL-E out of the Silver Screen: Understanding How Transformative Robot Sound Affects Human Perception | https://ieeexplore.ieee.org/document/9562082/ | [
"Brian J. Zhang",
"Nick Stargu",
"Samuel Brimhall",
"Lilian Chan",
"Jason Fick",
"Naomi T. Fitter",
"Brian J. Zhang",
"Nick Stargu",
"Samuel Brimhall",
"Lilian Chan",
"Jason Fick",
"Naomi T. Fitter"
] | Lovable robots in movies regularly beep, chirp, and whirr, yet robots in the real world rarely deploy such sounds. Despite preliminary work supporting the perceptual and objective benefits of intentionally-produced robot sound, relatively little research is ongoing in this area. In this paper, we systematically evaluate transformative robot sound across multiple robot archetypes and behaviors. We ... |
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