title
stringlengths 7
164
| detail_url
stringlengths 27
45
| author_list
sequencelengths 0
40
| abstract
stringlengths 0
403
|
|---|---|---|---|
KDFNet: Learning Keypoint Distance Field for 6D Object Pose Estimation | https://ieeexplore.ieee.org/document/9636489/ | [
"Xingyu Liu",
"Shun Iwase",
"Kris M. Kitani",
"Xingyu Liu",
"Shun Iwase",
"Kris M. Kitani"
] | We present KDFNet, a novel method for 6D object pose estimation from RGB images. To handle occlusion, many recent works have proposed to localize 2D keypoints through pixel-wise voting and solve a Perspective-n-Point (PnP) problem for pose estimation, which achieves leading performance. However, such voting process is direction-based and cannot handle long and thin objects where the direction inte... |
Precise Object Placement with Pose Distance Estimations for Different Objects and Grippers | https://ieeexplore.ieee.org/document/9635926/ | [
"Kilian Kleeberger",
"Jonathan Schnitzler",
"Muhammad Usman Khalid",
"Richard Bormann",
"Werner Kraus",
"Marco F. Huber",
"Kilian Kleeberger",
"Jonathan Schnitzler",
"Muhammad Usman Khalid",
"Richard Bormann",
"Werner Kraus",
"Marco F. Huber"
] | This paper introduces a novel approach for the grasping and precise placement of various known rigid objects using multiple grippers within highly cluttered scenes. Using a single depth image of the scene, our method estimates multiple 6D object poses together with an object class, a pose distance for object pose estimation, and a pose distance from a target pose for object placement for each auto... |
Learning to Detect Multi-Modal Grasps for Dexterous Grasping in Dense Clutter | https://ieeexplore.ieee.org/document/9636876/ | [
"Matt Corsaro",
"Stefanie Tellex",
"George Konidaris",
"Matt Corsaro",
"Stefanie Tellex",
"George Konidaris"
] | We propose an approach to multi-modal grasp detection that jointly predicts the probabilities that several types of grasps succeed at a given grasp pose. Given a partial point cloud of a scene, the algorithm proposes a set of feasible grasp candidates, then estimates the probabilities that a grasp of each type would succeed at each candidate pose. Predicting grasp success probabilities directly fr... |
Double-Dot Network for Antipodal Grasp Detection | https://ieeexplore.ieee.org/document/9636706/ | [
"Yao Wang",
"Yangtao Zheng",
"Boyang Gao",
"Di Huang",
"Yao Wang",
"Yangtao Zheng",
"Boyang Gao",
"Di Huang"
] | This paper proposes a new deep learning approach to antipodal grasp detection, named Double-Dot Network (DD-Net). It follows the recent anchor-free object detection framework, which does not depend on empirically pre-set anchors and thus allows more generalized and flexible prediction on unseen objects. Specifically, unlike the widely used 5-dimensional rectangle, the gripper configuration is defi... |
Neural Motion Prediction for In-flight Uneven Object Catching | https://ieeexplore.ieee.org/document/9635983/ | [
"Hongxiang Yu",
"Dashun Guo",
"Huan Yin",
"Anzhe Chen",
"Kechun Xu",
"Zexi Chen",
"Minhang Wang",
"Qimeng Tan",
"Yue Wang",
"Rong Xiong",
"Hongxiang Yu",
"Dashun Guo",
"Huan Yin",
"Anzhe Chen",
"Kechun Xu",
"Zexi Chen",
"Minhang Wang",
"Qimeng Tan",
"Yue Wang",
"Rong Xiong"
] | In-flight objects capture is extremely challenging. The robot is required to complete trajectory prediction, interception position calculation and motion planning within tens of milliseconds. As in-flight uneven objects are affected by various kinds of forces, which leads to the time-varying acceleration, motion prediction for them is difficult. In order to compensate the system’s non-linearity, w... |
Learning a Generative Transition Model for Uncertainty-Aware Robotic Manipulation | https://ieeexplore.ieee.org/document/9636623/ | [
"Lars Berscheid",
"Pascal Meißner",
"Torsten Kröger",
"Lars Berscheid",
"Pascal Meißner",
"Torsten Kröger"
] | Robot learning of real-world manipulation tasks remains challenging and time consuming, even though actions are often simplified by single-step manipulation primitives. In order to compensate the removed time dependency, we additionally learn an image-to-image transition model that is able to predict a next state including its uncertainty. We apply this approach to bin picking, the task of emptyin... |
Occlusion-Aware Search for Object Retrieval in Clutter | https://ieeexplore.ieee.org/document/9636230/ | [
"Wissam Bejjani",
"Wisdom C. Agboh",
"Mehmet R. Dogar",
"Matteo Leonetti",
"Wissam Bejjani",
"Wisdom C. Agboh",
"Mehmet R. Dogar",
"Matteo Leonetti"
] | We address the manipulation task of retrieving a target object from a cluttered shelf. When the target object is hidden, the robot must search through the clutter for retrieving it. Solving this task requires reasoning over the likely locations of the target object. It also requires physics reasoning over multi-object interactions and future occlusions. In this work, we present a data-driven hybri... |
Grasp Pose Detection from a Single RGB Image | https://ieeexplore.ieee.org/document/9636511/ | [
"Hu Cheng",
"Yingying Wang",
"Max Q.-H. Meng",
"Hu Cheng",
"Yingying Wang",
"Max Q.-H. Meng"
] | Grasp pose detection generates the position and orientation of the robot end-effector to grasp objects from the RGB or RGB-D image. In this paper, we propose a novel grasp pose detection network that generates 3-DOF grasp poses using the RGB image. The network follows the anchor-based object detection pipeline and incorporates the angle detection unit. Furthermore, we redesign the grasp angle pred... |
Learning When to Quit: Meta-Reasoning for Motion Planning | https://ieeexplore.ieee.org/document/9636864/ | [
"Yoonchang Sung",
"Leslie Pack Kaelbling",
"Tomás Lozano-Pérez",
"Yoonchang Sung",
"Leslie Pack Kaelbling",
"Tomás Lozano-Pérez"
] | Anytime motion planners are widely used in robotics. However, the relationship between their solution quality and computation time is not well understood, and thus, determining when to quit planning and start execution is unclear. In this paper, we address the problem of deciding when to stop deliberation under bounded computational capacity, so called meta-reasoning, for anytime motion planning. ... |
Joint Sampling and Trajectory Optimization over Graphs for Online Motion Planning | https://ieeexplore.ieee.org/document/9636064/ | [
"Kalyan Vasudev Alwala",
"Mustafa Mukadam",
"Kalyan Vasudev Alwala",
"Mustafa Mukadam"
] | Among the most prevalent motion planning techniques, sampling and trajectory optimization have emerged successful due to their ability to handle tight constraints and high-dimensional systems, respectively. However, limitations in sampling in higher dimensions and local minima issues in optimization have hindered their ability to excel beyond static scenes in offline settings. Here we consider hig... |
Path Planning for Robotic Manipulators in Dynamic Environments Using Distance Information | https://ieeexplore.ieee.org/document/9636730/ | [
"Nermin Covic",
"Bakir Lacevic",
"Dinko Osmankovic",
"Nermin Covic",
"Bakir Lacevic",
"Dinko Osmankovic"
] | In this paper, we present a novel algorithm – DRGBT (Dynamic Rapidly-exploring Generalized Bur Tree), intended for motion planning in dynamic environments. The main idea behind DRGBT lies in a so-called adaptive horizon, consisting of a set of prospective target nodes that belong to a predefined $\mathcal{C}$-space path, which originates from the current node. Each node is assigned a weight that d... |
Variable-Speed Traveling Salesman Problem for Vehicles with Curvature Constrained Trajectories | https://ieeexplore.ieee.org/document/9636762/ | [
"Kristýna Kučerová",
"Petr Váňa",
"Jan Faigl",
"Kristýna Kučerová",
"Petr Váňa",
"Jan Faigl"
] | This paper presents a novel approach to the multigoal trajectory planning for vehicles with curvature-constrained trajectories such as fixed-wing aircraft. In the existing formulation called the Dubins Traveling Salesman Problem (DTSP), the vehicle speed is assumed to be constant over the whole trajectory, and that does not allow adaptation of the turning radius of the trajectory between the targe... |
Risk-Aware Submodular Optimization for Stochastic Travelling Salesperson Problem | https://ieeexplore.ieee.org/document/9635957/ | [
"Rishab Balasubramanian",
"Lifeng Zhou",
"Pratap Tokekar",
"P. B. Sujit",
"Rishab Balasubramanian",
"Lifeng Zhou",
"Pratap Tokekar",
"P. B. Sujit"
] | We introduce a risk-aware variant of the Traveling Salesperson Problem (TSP), where the robot tour cost and reward have to be optimized simultaneously, while being subjected to uncertainty in both. We study the case where the rewards and the costs exhibit diminishing marginal gains, i.e., are submodular. Since the costs and the rewards are stochastic, we seek to maximize a risk metric known as Con... |
Fast Generation of Obstacle-Avoiding Motion Primitives for Quadrotors | https://ieeexplore.ieee.org/document/9636002/ | [
"Saurabh Upadhyay",
"Thomas Richardson",
"Arthur Richards",
"Saurabh Upadhyay",
"Thomas Richardson",
"Arthur Richards"
] | This work considers the problem of generating computationally efficient quadrotor motion primitives between a given pose (position, velocity, and acceleration) and a goal plane in the presence of obstacles. A new motion primitive tool based on the logistic curve is proposed and a closed-form analytic approach is developed to satisfy constraints on starting pose, goal plane, velocity, acceleration,... |
Roadmap for Visibility-based Target Tracking: Iterative Construction and Motion Strategy | https://ieeexplore.ieee.org/document/9636581/ | [
"Guillermo Laguna",
"Shashwata Mandal",
"Sourabh Bhattacharya",
"Guillermo Laguna",
"Shashwata Mandal",
"Sourabh Bhattacharya"
] | We consider the problem of generating a fixed path for a mobile observer in a polygonal environment that can maintain a line-of-sight with an unpredictable target. In contrast to purely off-line or on-line techniques, we propose a hierarchical tracking strategy in which an off-line path generation technique based on a RRT is coupled with an online feedback-control technique to generate trajectorie... |
Flocking and Collision Avoidance for a Dynamic Squad of Fixed-Wing UAVs Using Deep Reinforcement Learning | https://ieeexplore.ieee.org/document/9636183/ | [
"Chao Yan",
"Xiaojia Xiang",
"Chang Wang",
"Zhen Lan",
"Chao Yan",
"Xiaojia Xiang",
"Chang Wang",
"Zhen Lan"
] | Developing the flocking behavior for a dynamic squad of fixed-wing UAVs is still a challenge due to kinematic complexity and environmental uncertainty. In this paper, we deal with the decentralized flocking and collision avoidance problem through deep reinforcement learning (DRL). Specifically, we formulate a decentralized DRL-based decision making framework from the perspective of every follower,... |
Learning to Play Soccer From Scratch: Sample-Efficient Emergent Coordination Through Curriculum-Learning and Competition | https://ieeexplore.ieee.org/document/9636046/ | [
"Pavan Samtani",
"Francisco Leiva",
"Javier Ruiz-del-Solar",
"Pavan Samtani",
"Francisco Leiva",
"Javier Ruiz-del-Solar"
] | This work proposes a scheme that allows learning complex multi-agent behaviors in a sample efficient manner, applied to 2v2 soccer. The problem is formulated as a Markov game, and solved using deep reinforcement learning. We propose a basic multi-agent extension of TD3 for learning the policy of each player, in a decentralized manner. To ease learning, the task of 2v2 soccer is divided in three st... |
Hiding Leader’s Identity in Leader-Follower Navigation through Multi-Agent Reinforcement Learning | https://ieeexplore.ieee.org/document/9636314/ | [
"Ankur Deka",
"Wenhao Luo",
"Huao Li",
"Michael Lewis",
"Katia Sycara",
"Ankur Deka",
"Wenhao Luo",
"Huao Li",
"Michael Lewis",
"Katia Sycara"
] | Leader-follower navigation is a popular class of multi-robot algorithms where a leader robot leads the follower robots in a team. The leader has specialized capabilities or mission critical information (e.g. goal location) that the followers lack, and this makes the leader crucial for the mission’s success. However, this also makes the leader a vulnerability -an external adversary who wishes to sa... |
Moving Forward in Formation: A Decentralized Hierarchical Learning Approach to Multi-Agent Moving Together | https://ieeexplore.ieee.org/document/9636224/ | [
"Shanqi Liu",
"Licheng Wen",
"Jinhao Cui",
"Xuemeng Yang",
"Junjie Cao",
"Yong Liu",
"Shanqi Liu",
"Licheng Wen",
"Jinhao Cui",
"Xuemeng Yang",
"Junjie Cao",
"Yong Liu"
] | Multi-agent path finding in formation has many potential real-world applications like mobile warehouse robotics. However, previous multi-agent path finding (MAPF) methods hardly take formation into consideration. Further-more, they are usually centralized planners and require the whole state of the environment. Other decentralized partially observable approaches to MAPF are reinforcement learning ... |
Scalable Reinforcement Learning Policies for Multi-Agent Control | https://ieeexplore.ieee.org/document/9636344/ | [
"Christopher D. Hsu",
"Heejin Jeong",
"George J. Pappas",
"Pratik Chaudhari",
"Christopher D. Hsu",
"Heejin Jeong",
"George J. Pappas",
"Pratik Chaudhari"
] | We develop a Multi-Agent Reinforcement Learning (MARL) method to learn scalable control policies for target tracking. Our method can handle an arbitrary number of pursuers and targets; we show results for tasks consisting up to 1000 pursuers tracking 1000 targets. We use a decentralized, partially-observable Markov Decision Process framework to model pursuers as agents receiving partial observatio... |
ADD: A Fine-grained Dynamic Inference Architecture for Semantic Image Segmentation | https://ieeexplore.ieee.org/document/9636650/ | [
"Chi-Hsi Kung",
"Che-Rung Lee",
"Chi-Hsi Kung",
"Che-Rung Lee"
] | Dynamic inference that adaptively skips parts of model execution based on the complexity of input data can effectively reduce the computation cost of deep learning models during the inference. However, current architectures for dynamic inference only consider the exits at the block level, whose results may not be suitable for different applications. In this paper, we present the Auto-Dynamic-DeepL... |
COINet: Adaptive Segmentation with Co-Interactive Network for Autonomous Driving | https://ieeexplore.ieee.org/document/9636111/ | [
"Jie Liu",
"Xiaoqing Guo",
"Baopu Li",
"Yixuan Yuan",
"Jie Liu",
"Xiaoqing Guo",
"Baopu Li",
"Yixuan Yuan"
] | Semantic segmentation serves as a cornerstone for safety autonomous driving and has been achieved remarkable progress at the price of dense annotations. Unsupervised domain adaptation was widely utilized to addresses this labor-intensive problem, which transfers the knowledge learned from labeled synthetic datset to real-world without any annotations. However, most existing adaptation works predic... |
Category-Level 6D Object Pose Estimation via Cascaded Relation and Recurrent Reconstruction Networks | https://ieeexplore.ieee.org/document/9636212/ | [
"Jiaze Wang",
"Kai Chen",
"Qi Dou",
"Jiaze Wang",
"Kai Chen",
"Qi Dou"
] | Category-level 6D pose estimation, aiming to predict the location and orientation of unseen object instances, is fundamental to many scenarios such as robotic manipulation and augmented reality, yet still remains unsolved. Precisely recovering instance 3D model in the canonical space and accurately matching it with the observation is an essential point when estimating 6D pose for unseen objects. I... |
Unknown Object Segmentation from Stereo Images | https://ieeexplore.ieee.org/document/9636281/ | [
"Maximilian Durner",
"Wout Boerdijk",
"Martin Sundermeyer",
"Werner Friedl",
"Zoltán-Csaba Márton",
"Rudolph Triebel",
"Maximilian Durner",
"Wout Boerdijk",
"Martin Sundermeyer",
"Werner Friedl",
"Zoltán-Csaba Márton",
"Rudolph Triebel"
] | Although instance-aware perception is a key prerequisite for many autonomous robotic applications, most of the methods only partially solve the problem by focusing solely on known object categories. However, for robots interacting in dynamic and cluttered environments, this is not realistic and severely limits the range of potential applications. Therefore, we propose a novel object instance segme... |
Object Learning for 6D Pose Estimation and Grasping from RGB-D Videos of In-hand Manipulation | https://ieeexplore.ieee.org/document/9635884/ | [
"Timothy Patten",
"Kiru Park",
"Markus Leitner",
"Kevin Wolfram",
"Markus Vincze",
"Timothy Patten",
"Kiru Park",
"Markus Leitner",
"Kevin Wolfram",
"Markus Vincze"
] | Object models are highly useful for robots as they enable tasks such as detection, pose estimation and manipulation. However, models are not always easily available, especially in real-world domains of operation such as peoples’ homes. This work presents a pipeline to generate high-quality object reconstructions from human in-hand manipulation to alleviate the necessity of specialised or expensive... |
Online Monitoring of Object Detection Performance During Deployment | https://ieeexplore.ieee.org/document/9635940/ | [
"Quazi Marufur Rahman",
"Niko Sünderhauf",
"Feras Dayoub",
"Quazi Marufur Rahman",
"Niko Sünderhauf",
"Feras Dayoub"
] | During deployment, an object detector is expected to operate at a similar performance level reported on its testing dataset. However, when deployed onboard mobile robots that operate under varying and complex environmental conditions, the detector’s performance can fluctuate and occasionally degrade severely without warning. Undetected, this can lead the robot to take unsafe and risky actions base... |
Dynamic Lambda-Field: A Counterpart of the Bayesian Occupancy Grid for Risk Assessment in Dynamic Environments | https://ieeexplore.ieee.org/document/9636804/ | [
"Johann Laconte",
"Elie Randriamiarintsoa",
"Abderrahim Kasmi",
"François Pomerleau",
"Roland Chapuis",
"Christophe Debain",
"Romuald Aufrère",
"Johann Laconte",
"Elie Randriamiarintsoa",
"Abderrahim Kasmi",
"François Pomerleau",
"Roland Chapuis",
"Christophe Debain",
"Romuald Aufrère"
] | In the context of autonomous vehicles, one of the most crucial tasks is to estimate the risk of the undertaken action. While navigating in complex urban environments, the Bayesian occupancy grid is one of the most popular types of maps, where the information of occupancy is stored as the probability of collision. Although widely used, this kind of representation is not well suited for risk assessm... |
3D Radar Velocity Maps for Uncertain Dynamic Environments | https://ieeexplore.ieee.org/document/9636019/ | [
"Ransalu Senanayake",
"Kyle Beltran Hatch",
"Jason Zheng",
"Mykel J. Kochenderfer",
"Ransalu Senanayake",
"Kyle Beltran Hatch",
"Jason Zheng",
"Mykel J. Kochenderfer"
] | Future urban transportation concepts include a mixture of ground and air vehicles with varying degrees of autonomy in a congested environment. In such dynamic environments, occupancy maps alone are not sufficient for safe path planning. Safe and efficient transportation requires reasoning about the 3D flow of traffic and properly modeling uncertainty. Several different approaches can be taken for ... |
Extended VINS-Mono: A Systematic Approach for Absolute and Relative Vehicle Localization in Large-Scale Outdoor Environments | https://ieeexplore.ieee.org/document/9636776/ | [
"Mengwen He",
"Ragunathan Raj Rajkumar",
"Mengwen He",
"Ragunathan Raj Rajkumar"
] | We present a systematic approach called Extended VINS-Mono to utilize VINS-Mono, a state-of-the-art monocular visual-inertial relative localization method, targeting practical vehicle localization in large-scale outdoor road environments. Our proposed fusion approach associates multiple independent localization methods and provides multiple (projected) state estimates in a desired coordinate syste... |
Automated Type-Aware Traffic Speed Prediction based on Sparse Intelligent Camera System | https://ieeexplore.ieee.org/document/9636559/ | [
"Xiaoyang Xie",
"Kangjia Shao",
"Yang Wang",
"Fei Miao",
"Desheng Zhang",
"Xiaoyang Xie",
"Kangjia Shao",
"Yang Wang",
"Fei Miao",
"Desheng Zhang"
] | Many essential services for autonomous vehicles, e.g., navigation on high-quality maps, are designed based on the understanding of traffic conditions, e.g., travel time/speed on road segments, traffic flow, etc. However, most existing traffic condition models lack the consideration of the differentiation for vehicles with different types (e.g., personal vehicles or trucks) and thus they cannot sat... |
Vision-Based Control of an Unknown Suspended Payload with a Multirotor | https://ieeexplore.ieee.org/document/9636648/ | [
"J. F. Slabber",
"H. W. Jordaan",
"J. F. Slabber",
"H. W. Jordaan"
] | This paper presents a vision-based control strategy for a rotary-wing unmanned aerial vehicle (RUAV) transporting an unknown suspended payload. The suspended payload parameters, which include its mass and cable length, are unknown and direct measurements of its states are not available. A feedforward-feedback adaptive control strategy, that consists of a notch filter and linear quadratic Gaussian ... |
Gridlock-free Autonomous Parking Lots for Autonomous Vehicles | https://ieeexplore.ieee.org/document/9636591/ | [
"Tsz-Chiu Au",
"Tsz-Chiu Au"
] | Many cities suffer from a shortage of parking spaces. Research in high density parking (HDP) focuses on how to increase the capacity of parking lots by allowing vehicles to block each other but temporarily give way to other vehicles by driving autonomously upon request. Previous works on HDP did not consider mixing different parking strategies and ignored the possibility of gridlock when multiple ... |
Maneuver-based Trajectory Prediction for Self-driving Cars Using Spatio-temporal Convolutional Networks | https://ieeexplore.ieee.org/document/9636875/ | [
"Benedikt Mersch",
"Thomas Höllen",
"Kun Zhao",
"Cyrill Stachniss",
"Ribana Roscher",
"Benedikt Mersch",
"Thomas Höllen",
"Kun Zhao",
"Cyrill Stachniss",
"Ribana Roscher"
] | The ability to predict the future movements of other vehicles is a subconscious and effortless skill for humans and key to safe autonomous driving. Therefore, trajectory prediction for autonomous cars has gained a lot of attention in recent years. It is, however, still a hard task to achieve human-level performance. Interdependencies between vehicle behaviors and the multimodal nature of future in... |
NaturalNets: Simplified Biological Neural Networks for Learning Complex Tasks | https://ieeexplore.ieee.org/document/9636471/ | [
"Daniel Zimmermann",
"Björn Jürgens",
"Patrick Deubel",
"Anne Koziolek",
"Daniel Zimmermann",
"Björn Jürgens",
"Patrick Deubel",
"Anne Koziolek"
] | We present a new neural network architecture, called NaturalNet, which uses a simplified biological neuron model and consists of a set of nonlinear ordinary differential equations. We model the membrane potential of each neuron by integrating the in-flowing currents, but we do not consider ion channels, nor individual spikes. To keep the membrane potential within a defined value range, we introduc... |
Talk the talk and walk the walk: Dialogue-driven navigation in unknown indoor environments | https://ieeexplore.ieee.org/document/9636548/ | [
"Thomas Victor Ilyevsky",
"Jared Sigurd Johansen",
"Jeffrey Mark Siskind",
"Thomas Victor Ilyevsky",
"Jared Sigurd Johansen",
"Jeffrey Mark Siskind"
] | Prior work in natural-language-driven navigation demonstrates success in systems deployed in synthetic environments or applied to large datasets, both real and synthetic. However, there is an absence of such frameworks being deployed and rigorously tested in real environments, unknown a priori. In this paper, we present a novel framework that uses spoken dialogue with a real person to interpret a ... |
ORCHID: Optimisation of Robotic Control and Hardware In Design using Reinforcement Learning | https://ieeexplore.ieee.org/document/9635865/ | [
"Lucy Jackson",
"Celyn Walters",
"Steve Eckersley",
"Pete Senior",
"Simon Hadfield",
"Lucy Jackson",
"Celyn Walters",
"Steve Eckersley",
"Pete Senior",
"Simon Hadfield"
] | The successful performance of any system is dependant on the hardware of the agent, which is typically immutable during RL training. In this work, we present ORCHID (Optimisation of Robotic Control and Hardware In Design) which allows for truly simultaneous optimisation of hardware and control parameters in an RL pipeline. We show that by forming a complex differential path through a trajectory ro... |
Many-Joint Robot Arm Control with Recurrent Spiking Neural Networks | https://ieeexplore.ieee.org/document/9636001/ | [
"Manuel Traub",
"Robert Legenstein",
"Sebastian Otte",
"Manuel Traub",
"Robert Legenstein",
"Sebastian Otte"
] | In the paper, we show how scalable, low-cost trunk-like robotic arms can be constructed using only basic 3D-printing equipment and simple electronics. The design is based on uniform, stackable joint modules with three degrees of freedom each. Moreover, we present an approach for controlling these robots with recurrent spiking neural networks. At first, a spiking forward model learns motor-pose cor... |
Bootstrapping Motor Skill Learning with Motion Planning | https://ieeexplore.ieee.org/document/9636661/ | [
"Ben Abbatematteo",
"Eric Rosen",
"Stefanie Tellex",
"George Konidaris",
"Ben Abbatematteo",
"Eric Rosen",
"Stefanie Tellex",
"George Konidaris"
] | Learning a robot motor skill from scratch is impractically slow; so much so that in practice, learning must typically be bootstrapped using human demonstration. However, relying on human demonstration necessarily degrades the autonomy of robots that must learn a wide variety of skills over their operational lifetimes. We propose using kinematic motion planning as a completely autonomous, sample ef... |
Towards Safe Navigation Through Crowded Dynamic Environments | https://ieeexplore.ieee.org/document/9636102/ | [
"Zhanteng Xie",
"Pujie Xin",
"Philip Dames",
"Zhanteng Xie",
"Pujie Xin",
"Philip Dames"
] | This paper proposes a novel neural network-based control policy to enable a mobile robot to navigate safety through environments filled with both static obstacles, such as tables and chairs, and dense crowds of pedestrians. The network architecture uses early fusion to combine a short history of lidar data with kinematic data about nearby pedestrians. This kinematic data is key to enable safe robo... |
Self-Balancing Online Dataset for Incremental Driving Intelligence | https://ieeexplore.ieee.org/document/9636525/ | [
"Hyung-Suk Yoon",
"Chan Kim",
"Seong-Woo Kim",
"Seung-Woo Seo",
"Hyung-Suk Yoon",
"Chan Kim",
"Seong-Woo Kim",
"Seung-Woo Seo"
] | Autonomous driving with imitation learning is vulnerable to the quality of an expert dataset. Typical driving involves situations or online data that are biased toward specific scenarios such as lane following or stop. This property causes an imbalance in the driving dataset, and it is highly likely to deteriorate the performance of autonomous driving with imitation learning. In this paper, we pro... |
Turning an Articulated 3-PPSR Manipulator into a Parallel Continuum Robot | https://ieeexplore.ieee.org/document/9636596/ | [
"Oscar F. Gallardo",
"Benjamin Mauzé",
"Redwan Dahmouche",
"Christian Duriez",
"Guillaume J. Laurent",
"Oscar F. Gallardo",
"Benjamin Mauzé",
"Redwan Dahmouche",
"Christian Duriez",
"Guillaume J. Laurent"
] | Parallel Continuum Robots (PCR) have received a lot of attention in recent years. This paper presents a new 6-degrees-of-freedom PCR derived from the conventional 3-PPSR parallel manipulator. This robot is driven by three limbs consisting of two flexible rods each and replacing the spherical and revolute joints of the original version. Each limb is mounted onto two linear axes arranged in series. ... |
Multifunctional Robotic Glove with Active-Passive Training Modes for Hand Rehabilitation and Assistance | https://ieeexplore.ieee.org/document/9636437/ | [
"Yongkang Jiang",
"Diansheng Chen",
"Junlin Ma",
"Zhe Liu",
"Yazhe Luo",
"Jian Li",
"Yingtian Li",
"Yongkang Jiang",
"Diansheng Chen",
"Junlin Ma",
"Zhe Liu",
"Yazhe Luo",
"Jian Li",
"Yingtian Li"
] | Soft robotic gloves have shown great advantages in assisting individuals with hand pathologies to perform continuous exercises to restore their hand functions, which could considerably accelerate the rehabilitation process and reduce the costs. However, single rehabilitation mode, difficulty in achieving multiple degrees-of-freedom (DoF) motion, and the lack of high-fidelity feedback still challen... |
Climbot-Ω: A Soft Robot with Novel Grippers and Rigid-compliantly Constrained Body for Climbing on Various Poles | https://ieeexplore.ieee.org/document/9636566/ | [
"Manjia Su",
"Yu Qiu",
"Yisheng Guan",
"Haifei Zhu",
"Zhi Liu",
"Manjia Su",
"Yu Qiu",
"Yisheng Guan",
"Haifei Zhu",
"Zhi Liu"
] | Soft climbing robots have been attracting increasing attention in soft robotics community, and a lot of prototypes been proposed with basic climbing function implemented. Climbing on poles is a challenge with soft robots, and the capability of current pole-climbing soft robots needs to be improved in terms of adaptability to various poles and deformation controllability or constraining of the soft... |
Soft Retraction Device and Internal Camera Mount for Everting Vine Robots | https://ieeexplore.ieee.org/document/9636697/ | [
"William E. Heap",
"Nicholas D. Naclerio",
"Margaret M. Coad",
"Sang-Goo Jeong",
"Elliot W. Hawkes",
"William E. Heap",
"Nicholas D. Naclerio",
"Margaret M. Coad",
"Sang-Goo Jeong",
"Elliot W. Hawkes"
] | Soft, tip-extending, pneumatic "vine robots" that grow via eversion are well suited for navigating cluttered environments. Two key mechanisms that add to the robot’s functionality are a tip-mounted retraction device that allows the growth process to be reversed, and a tip-mounted camera that enables vision. However, previous designs used rigid, relatively heavy electromechanical retraction devices... |
Partial Formation of Hydroxyapatite on Poly (Vinyl Alcohol) Hydrogel for Intensive Motions of Biomimetic Soft Robots | https://ieeexplore.ieee.org/document/9636368/ | [
"Towa Ueno",
"Haruka Oda",
"Yuya Morimoto",
"Shoji Takeuchi",
"Towa Ueno",
"Haruka Oda",
"Yuya Morimoto",
"Shoji Takeuchi"
] | The fabrication method to utilize poly (vinyl alcohol) hydrogels with additional stiff parts in a single structure for hydrogel-based soft robots to realize an intensive motion with elastic energy is proposed in this paper. An inorganic material which is often seen in the hard tissues of our body; hydroxyapatite, was partially formed on a hydrogel with a simple procedure of alternatingly soaking a... |
Multi-Object Grasping – Estimating the Number of Objects in a Robotic Grasp | https://ieeexplore.ieee.org/document/9636777/ | [
"Tianze Chen",
"Adheesh Shenoy",
"Anzhelika Kolinko",
"Syed Shah",
"Yu Sun",
"Tianze Chen",
"Adheesh Shenoy",
"Anzhelika Kolinko",
"Syed Shah",
"Yu Sun"
] | A human hand can grasp a desired number of objects at once from a pile based solely on tactile sensing. To do so, a robot needs to make a grasp in a pile, sense the number of objects in the grasp before lifting, and predict how many will remain in the grasp after lifting. It is a very challenging problem because when making the prediction, the robotic hand is still in the pile and the objects in t... |
PackerBot: Variable-Sized Product Packing with Heuristic Deep Reinforcement Learning | https://ieeexplore.ieee.org/document/9635914/ | [
"Zifei Yang",
"Shuo Yang",
"Shuai Song",
"Wei Zhang",
"Ran Song",
"Jiyu Cheng",
"Yibin Li",
"Zifei Yang",
"Shuo Yang",
"Shuai Song",
"Wei Zhang",
"Ran Song",
"Jiyu Cheng",
"Yibin Li"
] | Product packing is a typical application in ware-house automation that aims to pick objects from unstructured piles and place them into bins with optimized placing policy. However, it still remains a significant challenge to finish the product packing tasks in general logistics scenarios where the objects are variable-sized and the configurations are complex. In this work, we present the PackerBot... |
A Soft Robotic Hip Exosuit (SR-HExo) to Assist Hip Flexion and Extension during Human Locomotion | https://ieeexplore.ieee.org/document/9636225/ | [
"Carly M. Thalman",
"Lily Baye-Wallace",
"Hyunglae Lee",
"Carly M. Thalman",
"Lily Baye-Wallace",
"Hyunglae Lee"
] | This paper presents the design, fabrication, and preliminary results of a soft hip exosuit to assist hip flexion and extension during walking. The exosuit uses soft and compliant materials to create a wearable robot that has a low profile, low mass, and is highly flexible to freely move with the user’s natural range of motion. The Soft Robotic Hip Exosuit (SR-HExo) consists of flat fabric pneumati... |
Muscle synergies enable accurate joint moment prediction using few electromyography sensors | https://ieeexplore.ieee.org/document/9636696/ | [
"Yi-Xing Liu",
"Elena M. Gutierrez-Farewik",
"Yi-Xing Liu",
"Elena M. Gutierrez-Farewik"
] | There is an increasing demand for accurate prediction of joint moments using wearable sensors for robotic exoskeletons to achieve precise control and for rehabilitation care to remotely monitor users’ condition. In this study, we used electromyography (EMG) signals to first identify muscle synergies, then used them to train of a long short-term memory network to predict knee joint moments during w... |
F-VESPA: A Kinematic-based Algorithm for Real-time Heel-strike Detection During Walking | https://ieeexplore.ieee.org/document/9636335/ | [
"Chrysostomos Karakasis",
"Panagiotis Artemiadis",
"Chrysostomos Karakasis",
"Panagiotis Artemiadis"
] | With over 10 million people currently suffering from significant long-term gait disability in the United States only, robot-assisted rehabilitation and wearable devices are increasingly gaining attention as a mean to regain functional mobility. Since these devices work collaborative and synchronously with the human gait, it is necessary to be able to detect gait events, such as heel-strikes, in re... |
Knee-stretched Biped Gait Generation along Spatially Quantized Curves | https://ieeexplore.ieee.org/document/9636872/ | [
"Yuki Onishi",
"Shuuji Kajita",
"Tatsuya Ibuki",
"Mitsuji Sampei",
"Yuki Onishi",
"Shuuji Kajita",
"Tatsuya Ibuki",
"Mitsuji Sampei"
] | This paper presents a method for biped gait generation along a predefined curve with fully stretched knees. First, we design a spatial gait pattern as a function of the traveled distance on the path without considering dynamics. Then, a consistent dynamic walking motion is obtained by optimization that minimizes the zero-moment point and the speed errors while considering the trade-off between kin... |
Robust Feedback Motion Policy Design Using Reinforcement Learning on a 3D Digit Bipedal Robot | https://ieeexplore.ieee.org/document/9636467/ | [
"Guillermo A. Castillo",
"Bowen Weng",
"Wei Zhang",
"Ayonga Hereid",
"Guillermo A. Castillo",
"Bowen Weng",
"Wei Zhang",
"Ayonga Hereid"
] | In this paper, a hierarchical and robust framework for learning bipedal locomotion is presented and successfully implemented on the 3D biped robot Digit built by Agility Robotics. We propose a cascade-structure controller that combines the learning process with intuitive feedback regulations. This design allows the framework to realize robust and stable walking with a reduced-dimensional state and... |
Learning When to Switch: Composing Controllers to Traverse a Sequence of Terrain Artifacts | https://ieeexplore.ieee.org/document/9636233/ | [
"Brendan Tidd",
"Akansel Cosgun",
"Jürgen Leitner",
"Nicolas Hudson",
"Brendan Tidd",
"Akansel Cosgun",
"Jürgen Leitner",
"Nicolas Hudson"
] | Legged robots often use separate control policies that are highly engineered for traversing difficult terrain such as stairs, gaps, and steps, where switching between policies is only possible when the robot is in a region that is common to adjacent controllers. Deep Reinforcement Learning (DRL) is a promising alternative to hand-crafted control design, though typically requires the full set of te... |
Impact Invariant Control with Applications to Bipedal Locomotion | https://ieeexplore.ieee.org/document/9636094/ | [
"William Yang",
"Michael Posa",
"William Yang",
"Michael Posa"
] | When legged robots impact their environment, they undergo large changes in their velocities in a small amount of time. Measuring and applying feedback to these velocities is challenging, and is further complicated due to uncertainty in the impact model and impact timing. This work proposes a general framework for adapting feedback control during impact by projecting the control objectives to a sub... |
Learning Linear Policies for Robust Bipedal Locomotion on Terrains with Varying Slopes | https://ieeexplore.ieee.org/document/9636070/ | [
"Lokesh Krishna",
"Utkarsh A. Mishra",
"Guillermo A. Castillo",
"Ayonga Hereid",
"Shishir Kolathaya",
"Lokesh Krishna",
"Utkarsh A. Mishra",
"Guillermo A. Castillo",
"Ayonga Hereid",
"Shishir Kolathaya"
] | In this paper, with a view toward deployment of light-weight control frameworks for bipedal walking robots, we realize end-foot trajectories that are shaped by a single linear feedback policy. We learn this policy via a model-free and a gradient free learning algorithm, Augmented Random Search (ARS), in the two robot platforms Rabbit and Digit. Our contributions are two-fold: a) By using torso and... |
Contact Tracing: A Low Cost Reconstruction Framework for Surface Contact Interpolation | https://ieeexplore.ieee.org/document/9636313/ | [
"Arjun Lakshmipathy",
"Dominik Bauer",
"Nancy S. Pollard",
"Arjun Lakshmipathy",
"Dominik Bauer",
"Nancy S. Pollard"
] | We present a novel, low cost framework for reconstructing surface contact movements during in-hand manipulations. Unlike many existing methods focused on hand pose tracking, ours models the behavior of contact patches, and by doing so is the first to obtain detailed contact tracking estimates for multi-contact manipulations. Our framework is highly accessible, requiring only low cost, readily avai... |
Real-Time Physically-Accurate Simulation of Robotic Snap Connection Process | https://ieeexplore.ieee.org/document/9636246/ | [
"Minji Lee",
"Jeongmin Lee",
"Jaemin Yoon",
"Dongjun Lee",
"Minji Lee",
"Jeongmin Lee",
"Jaemin Yoon",
"Dongjun Lee"
] | We propose a novel real-time physically-accurate simulation framework for the snap connection process. For this, we first notice the peculiarities of the process, namely, small/smooth deformation, stiff connector and segmented contact. We then design our simulation to fully exploit these peculiarities by adopting the following strategies: 1) the technique of passive midpoint integration (PMI [1]),... |
Fundamental Challenges in Deep Learning for Stiff Contact Dynamics | https://ieeexplore.ieee.org/document/9636383/ | [
"Mihir Parmar",
"Mathew Halm",
"Michael Posa",
"Mihir Parmar",
"Mathew Halm",
"Michael Posa"
] | Frictional contact has been extensively studied as the core underlying behavior of legged locomotion and manipulation, and its nearly-discontinuous nature makes planning and control difficult even when an accurate model of the robot is available. Here, we present empirical evidence that learning an accurate model in the first place can be confounded by contact, as modern deep learning approaches a... |
Computationally Efficient HQP-based Whole-body Control Exploiting the Operational-space Formulation | https://ieeexplore.ieee.org/document/9636867/ | [
"Yisoo Lee",
"Junewhee Ahn",
"Jinoh Lee",
"Jaeheung Park",
"Yisoo Lee",
"Junewhee Ahn",
"Jinoh Lee",
"Jaeheung Park"
] | This paper proposes a novel and practical approach to enhance the computational efficiency of the hierarchical quadratic programming (HQP)-based whole-body control. The HQP method is known to offer control solutions satisfying strict priority with various constraints for multiple-tasks execution. However, it inherently comes at the price of high computation time to solve QP optimization problems i... |
Towards an Online Framework for Changing-Contact Robot Manipulation Tasks | https://ieeexplore.ieee.org/document/9636278/ | [
"Saif Sidhik",
"Mohan Sridharan",
"Dirk Ruiken",
"Saif Sidhik",
"Mohan Sridharan",
"Dirk Ruiken"
] | We describe a framework for changing-contact robot manipulation tasks, which require the robot to make and break contacts with objects and surfaces. The discontinuous interaction dynamics of such tasks make it difficult to construct and use a single dynamics model or control strategy for such tasks. For any target motion trajectory, our framework incrementally improves its prediction of when conta... |
Toward battery-free flight: Duty cycled recharging of small drones | https://ieeexplore.ieee.org/document/9636087/ | [
"Nishant Elkunchwar",
"Suvesha Chandrasekaran",
"Vikram Iyer",
"Sawyer B. Fuller",
"Nishant Elkunchwar",
"Suvesha Chandrasekaran",
"Vikram Iyer",
"Sawyer B. Fuller"
] | Constrained battery life on current Unmanned Aerial Vehicles (drones) limits the time they can operate and distance they can travel. We address this challenge by harvesting solar power to enable duty-cycled operation on a palm-sized drone. We present a scaling analysis that suggests that more solar power can be collected per unit mass of the drone as scale reduces, favoring small drones. By chargi... |
Aggressive Visual Perching with Quadrotors on Inclined Surfaces | https://ieeexplore.ieee.org/document/9636690/ | [
"Jeffrey Mao",
"Guanrui Li",
"Stephen Nogar",
"Christopher Kroninger",
"Giuseppe Loianno",
"Jeffrey Mao",
"Guanrui Li",
"Stephen Nogar",
"Christopher Kroninger",
"Giuseppe Loianno"
] | Autonomous Micro Aerial Vehicles (MAVs) have the potential to be employed for surveillance and monitoring tasks. By perching and staring on one or multiple locations aerial robots can save energy while concurrently increasing their overall mission time without actively flying. In this paper, we address the estimation, planning, and control problems for autonomous perching on inclined surfaces with... |
Visibility-aware Trajectory Optimization with Application to Aerial Tracking | https://ieeexplore.ieee.org/document/9636753/ | [
"Qianhao Wang",
"Yuman Gao",
"Jialin Ji",
"Chao Xu",
"Fei Gao",
"Qianhao Wang",
"Yuman Gao",
"Jialin Ji",
"Chao Xu",
"Fei Gao"
] | The visibility of targets determines performance and even success rate of various applications, such as active slam, exploration, and target tracking. Therefore, it is crucial to take the visibility of targets into explicit account in trajectory planning. In this paper, we propose a general metric for target visibility, considering observation distance and angle as well as occlusion effect. We for... |
Gamma-Ray Imaging with Spatially Continuous Intensity Statistics | https://ieeexplore.ieee.org/document/9635973/ | [
"Marcus Greiff",
"Emil Rofors",
"Anders Robertsson",
"Rolf Johansson",
"Rikard Tyllström",
"Marcus Greiff",
"Emil Rofors",
"Anders Robertsson",
"Rolf Johansson",
"Rikard Tyllström"
] | Novel methods for the inference of radiation intensity functions defined over known surfaces are proposed, intended for use in surveying applications with mobile spectrometers. Previous approaches, based on the maximum likelihood expectation maximization (ML-EM) framework with Poisson likelihoods, are extended to better handle spatially continuous intensity statistics using ideas from Gaussian fil... |
3D Human Reconstruction in the Wild with Collaborative Aerial Cameras | https://ieeexplore.ieee.org/document/9636745/ | [
"Cherie Ho",
"Andrew Jong",
"Harry Freeman",
"Rohan Rao",
"Rogerio Bonatti",
"Sebastian Scherer",
"Cherie Ho",
"Andrew Jong",
"Harry Freeman",
"Rohan Rao",
"Rogerio Bonatti",
"Sebastian Scherer"
] | Aerial vehicles are revolutionizing applications that require capturing the 3D structure of dynamic targets in the wild, such as sports, medicine and entertainment. The core challenges in developing a motion-capture system that operates in outdoors environments are: (1) 3D inference requires multiple simultaneous viewpoints of the target, (2) occlusion caused by obstacles is frequent when tracking... |
Non-Prehensile Manipulation of Cuboid Objects Using a Catenary Robot | https://ieeexplore.ieee.org/document/9636820/ | [
"Gustavo A. Cardona",
"Diego S. D’Antonio",
"Cristian-Ioan Vasile",
"David Saldaña",
"Gustavo A. Cardona",
"Diego S. D’Antonio",
"Cristian-Ioan Vasile",
"David Saldaña"
] | Transporting objects using quadrotors with cables has been widely studied in the literature. However, most of those approaches assume that the cables are previously attached to the load by human intervention. In tasks where multiple objects need to be moved, the efficiency of the robotic system is constrained by the requirement of manual labor. Our approach uses a non-stretchable cable connected t... |
Passivity-based control for haptic teleoperation of a legged manipulator in presence of time-delays | https://ieeexplore.ieee.org/document/9636642/ | [
"Mattia Risiglione",
"Jean-Pierre Sleiman",
"Maria Vittoria Minniti",
"Burak Çizmeci",
"Douwe Dresscher",
"Marco Hutter",
"Mattia Risiglione",
"Jean-Pierre Sleiman",
"Maria Vittoria Minniti",
"Burak Çizmeci",
"Douwe Dresscher",
"Marco Hutter"
] | When dealing with the haptic teleoperation of multi-limbed mobile manipulators, the problem of mitigating the destabilizing effects arising from the communication link between the haptic device and the remote robot has not been properly addressed. In this work, we propose a passive control architecture to haptically teleoperate a legged mobile manipulator, while remaining stable in the presence of... |
SnakeRaven: Teleoperation of a 3D Printed Snake-like Manipulator Integrated to the RAVEN II Surgical Robot | https://ieeexplore.ieee.org/document/9636878/ | [
"Andrew Razjigaev",
"Ajay K. Pandey",
"David Howard",
"Jonathan Roberts",
"Liao Wu",
"Andrew Razjigaev",
"Ajay K. Pandey",
"David Howard",
"Jonathan Roberts",
"Liao Wu"
] | Telerobotic systems combined with miniaturised snake-like or elephant-trunk robotic arms can improve the ergonomics and accessibility in minimally invasive surgical tasks such as knee arthroscopy. Such systems, however, are usually designed in a specific and integral approach, making it expensive to adapt to various procedures or patient anatomies. 3D printed instruments with a detachable design c... |
Learning to Guide Human Attention on Mobile Telepresence Robots with 360° Vision | https://ieeexplore.ieee.org/document/9636607/ | [
"Kishan Chandan",
"Jack Albertson",
"Xiaohan Zhang",
"Xiaoyang Zhang",
"Yao Liu",
"Shiqi Zhang",
"Kishan Chandan",
"Jack Albertson",
"Xiaohan Zhang",
"Xiaoyang Zhang",
"Yao Liu",
"Shiqi Zhang"
] | Mobile telepresence robots (MTRs) allow people to navigate and interact with a remote environment that is in a place other than the person’s true location. Thanks to the recent advances in 360° vision, many MTRs are now equipped with an all-degree visual perception capability. However, people’s visual field horizontally spans only about 120° of the visual field captured by the robot. To bridge thi... |
Learning to Arbitrate Human and Robot Control using Disagreement between Sub-Policies | https://ieeexplore.ieee.org/document/9636049/ | [
"Yoojin Oh",
"Marc Toussaint",
"Jim Mainprice",
"Yoojin Oh",
"Marc Toussaint",
"Jim Mainprice"
] | In the context of teleoperation, arbitration refers to deciding how to blend between human and autonomous robot commands. We present a reinforcement learning solution that learns an optimal arbitration strategy that allocates more control authority to the human when the robot comes across a decision point in the task. A decision point is where the robot encounters multiple options (sub-policies), ... |
NimbRo Avatar: Interactive Immersive Telepresence with Force-Feedback Telemanipulation | https://ieeexplore.ieee.org/document/9636191/ | [
"Max Schwarz",
"Christian Lenz",
"Andre Rochow",
"Michael Schreiber",
"Sven Behnke",
"Max Schwarz",
"Christian Lenz",
"Andre Rochow",
"Michael Schreiber",
"Sven Behnke"
] | Robotic avatars promise immersive teleoperation with human-like manipulation and communication capabilities. We present such an avatar system, based on the key components of immersive 3D visualization and transparent force-feedback telemanipulation. Our avatar robot features an anthropomorphic bimanual arm configuration with dexterous hands. The remote human operator drives the arms and fingers th... |
Robust SLAM Systems: Are We There Yet? | https://ieeexplore.ieee.org/document/9636814/ | [
"Mihai Bujanca",
"Xuesong Shi",
"Matthew Spear",
"Pengpeng Zhao",
"Barry Lennox",
"Mikel Luján",
"Mihai Bujanca",
"Xuesong Shi",
"Matthew Spear",
"Pengpeng Zhao",
"Barry Lennox",
"Mikel Luján"
] | Progress in the last decade has brought about significant improvements in the accuracy and speed of SLAM systems, broadening their mapping capabilities. Despite these advancements, long-term operation remains a major challenge, primarily due to the wide spectrum of perturbations robotic systems may encounter.Increasing the robustness of SLAM algorithms is an ongoing effort, however it usually addr... |
Evaluating the Impact of Semantic Segmentation and Pose Estimation on Dense Semantic SLAM | https://ieeexplore.ieee.org/document/9636271/ | [
"Suman Raj Bista",
"David Hall",
"Ben Talbot",
"Haoyang Zhang",
"Feras Dayoub",
"Niko Sünderhauf",
"Suman Raj Bista",
"David Hall",
"Ben Talbot",
"Haoyang Zhang",
"Feras Dayoub",
"Niko Sünderhauf"
] | Recent Semantic SLAM methods combine classical geometry-based estimation with deep learning-based object detection or semantic segmentation. In this paper we evaluate the quality of semantic maps generated by state-of-the-art class-and instance-aware dense semantic SLAM algorithms whose codes are publicly available and explore the impacts both semantic segmentation and pose estimation have on the ... |
Overlap Displacement Error: Are Your SLAM Poses Map-Consistent? | https://ieeexplore.ieee.org/document/9636833/ | [
"Christian Mostegel",
"Jianbo Ye",
"Yu Luo",
"Yang Liu",
"Christian Mostegel",
"Jianbo Ye",
"Yu Luo",
"Yang Liu"
] | Localization is an essential module that supports many intelligent functions of a mobile robot such as transportation or inspection. However, justifying that a localization module is sufficiently accurate for supporting all downstream tasks is one of the most difficult questions to answer in practice. To overcome this problem, we move away from the traditional calculation of pose errors and propos... |
Error Diagnosis of Deep Monocular Depth Estimation Models | https://ieeexplore.ieee.org/document/9636673/ | [
"Jagpreet Chawla",
"Nikhil Thakurdesai",
"Anuj Godase",
"Md Reza",
"David Crandall",
"Soon-Heung Jung",
"Jagpreet Chawla",
"Nikhil Thakurdesai",
"Anuj Godase",
"Md Reza",
"David Crandall",
"Soon-Heung Jung"
] | Estimating depth from a monocular image is an ill-posed problem: when the camera projects a 3D scene onto a 2D plane, depth information is inherently and permanently lost. Nevertheless, recent work has shown impressive results in estimating 3D structure from 2D images using deep learning. In this paper, we put on an introspective hat and analyze state-of-the-art monocular depth estimation models i... |
New Metrics for Industrial Depth Sensors Evaluation for Precise Robotic Applications | https://ieeexplore.ieee.org/document/9636322/ | [
"Konrad P Cop",
"Arne Peters",
"Bare L Žagar",
"Daniel Hettegger",
"Alois C Knoll",
"Konrad P Cop",
"Arne Peters",
"Bare L Žagar",
"Daniel Hettegger",
"Alois C Knoll"
] | Precise perception is one of the key enablers of autonomous robotic operations. The right selection of sensors significantly influences the overall performance of the system. This paper provides a systematic approach for evaluation of various sensors available on the market. The main focus is to assess the performance in use cases of short to medium distance operations, especially relevant for pre... |
I3SA: The Increased Step Size Stability Assessment Benchmark and its Application to the Humanoid Robot REEM-C | https://ieeexplore.ieee.org/document/9636429/ | [
"Felix Aller",
"Monika Harant",
"Sebastian Sontag",
"Matthew Millard",
"Katja Mombaur",
"Felix Aller",
"Monika Harant",
"Sebastian Sontag",
"Matthew Millard",
"Katja Mombaur"
] | The implementation of stable locomotion on humanoid robots is a difficult task. This is complicated by the fact that there is no uniform method for analyzing a robot and its control architecture and for calculating indicators to quantify performance of flat ground walking. Moreover, there is no widely accepted indicator do distinct between a stable and unstable state of the robot. We propose the I... |
Interpretable Trade-offs Between Robot Task Accuracy and Compute Efficiency | https://ieeexplore.ieee.org/document/9636580/ | [
"Bineet Ghosh",
"Sandeep Chinchali",
"Parasara Sridhar Duggirala",
"Bineet Ghosh",
"Sandeep Chinchali",
"Parasara Sridhar Duggirala"
] | A robot can invoke heterogeneous computation resources such as CPUs, cloud GPU servers, or even human computation for achieving a high-level goal. The problem of invoking an appropriate computation model so that it will successfully complete a task while keeping its compute and energy costs within a budget is called a model selection problem. In this paper, we present an optimal solution to the mo... |
Towards Robust Visual Diver Detection Onboard Autonomous Underwater Robots: Assessing the Effects of Models and Data1 | https://ieeexplore.ieee.org/document/9636099/ | [
"Karin de Langis",
"Michael Fulton",
"Junaed Sattar",
"Karin de Langis",
"Michael Fulton",
"Junaed Sattar"
] | Deep neural networks are the leading solution to the object detection problem. However, challenges arise when applying these networks to the kind of real-time, first-person video data that a robotic platform must process: specifically, detections may not be consistent from frame to frame, and objects may frequently appear at viewpoints that are particularly challenging for the model, resulting in ... |
Predicting the Future Motion of Divers for Enhanced Underwater Human-Robot Collaboration | https://ieeexplore.ieee.org/document/9636374/ | [
"Tanmay Agarwal",
"Michael Fulton",
"Junaed Sattar",
"Tanmay Agarwal",
"Michael Fulton",
"Junaed Sattar"
] | Autonomous Underwater Vehicles (AUVs) can be effective collaborators to human scuba divers in many applications, such as environmental surveying, mapping, or infrastructure repair. However, for these applications to be realized in the real world, it is essential that robots are able to both lead and follow their human collaborators. Current algorithms for diver following are not robust to non-unif... |
Efficient LiDAR-based In-water Obstacle Detection and Segmentation by Autonomous Surface Vehicles in Aquatic Environments | https://ieeexplore.ieee.org/document/9636028/ | [
"Mingi Jeong",
"Alberto Quattrini Li",
"Mingi Jeong",
"Alberto Quattrini Li"
] | Identifying in-water obstacles is fundamental for safe navigation of Autonomous Surface Vehicles (ASVs). This paper presents a model-free method for segmenting individual in-water objects (e.g., swimmers, buoys, boats) and shorelines from LiDAR sensor data. To reduce the computational requirement, our method first converts the 3D point cloud into a 2D spherical projection image. Then, an algorithm... |
ShorelineNet: An Efficient Deep Learning Approach for Shoreline Semantic Segmentation for Unmanned Surface Vehicles | https://ieeexplore.ieee.org/document/9636614/ | [
"Linghong Yao",
"Dimitrios Kanoulas",
"Ze Ji",
"Yuanchang Liu",
"Linghong Yao",
"Dimitrios Kanoulas",
"Ze Ji",
"Yuanchang Liu"
] | This paper introduces a novel deep learning approach to semantic segmentation of the shoreline environments with a high frames-per-second (fps) performance, making the approach readily applicable to autonomous navigation for Unmanned Surface Vehicles (USV). The proposed ShorelineNet is an efficient deep neural network of high performance relying only on visual input. ShorelineNet uses monocular vi... |
AquaVis: A Perception-Aware Autonomous Navigation Framework for Underwater Vehicles | https://ieeexplore.ieee.org/document/9636124/ | [
"Marios Xanthidis",
"Michail Kalaitzakis",
"Nare Karapetyan",
"James Johnson",
"Nikolaos Vitzilaios",
"Jason M. O’Kane",
"Ioannis Rekleitis",
"Marios Xanthidis",
"Michail Kalaitzakis",
"Nare Karapetyan",
"James Johnson",
"Nikolaos Vitzilaios",
"Jason M. O’Kane",
"Ioannis Rekleitis"
] | Visual monitoring operations underwater require both observing the objects of interest in close-proximity, and tracking the few feature-rich areas necessary for state estimation. This paper introduces the first navigation framework, called AquaVis, that produces on-line visibility-aware motion plans that enable Autonomous Underwater Vehicles (AUVs) to track multiple visual objectives with an arbit... |
Accurate Visual-Inertial SLAM by Manhattan Frame Re-identification | https://ieeexplore.ieee.org/document/9636245/ | [
"Xiongfeng Peng",
"Zhihua Liu",
"Qiang Wang",
"Yun-Tae Kim",
"Hong-Seok Lee",
"Xiongfeng Peng",
"Zhihua Liu",
"Qiang Wang",
"Yun-Tae Kim",
"Hong-Seok Lee"
] | Most of the state-of-the-art visual-inertial SLAM methods pay less attention to the scene structure of man-made environments. In this paper, based on the assumption of multiple local Manhattan worlds (MWs), we propose a Manhattan frame (MF) re-identification method to build relative rotation constraints between MF matching pairs and tightly couple these constraints into global bundle adjust module... |
SymbioLCD: Ensemble-Based Loop Closure Detection using CNN-Extracted Objects and Visual Bag-of-Words | https://ieeexplore.ieee.org/document/9636622/ | [
"Jonathan J.Y. Kim",
"Martin Urschler",
"Patricia J. Riddle",
"Jörg S. Wicker",
"Jonathan J.Y. Kim",
"Martin Urschler",
"Patricia J. Riddle",
"Jörg S. Wicker"
] | Loop closure detection is an essential tool of Simultaneous Localization and Mapping (SLAM) to minimize drift in its localization. Many state-of-the-art loop closure detection (LCD) algorithms use visual Bag-of-Words (vBoW), which is robust against partial occlusions in a scene but cannot perceive the semantics or spatial relationships between feature points. CNN object extraction can address thos... |
Consensus-Informed Optimization Over Mixtures for Ambiguity-Aware Object SLAM | https://ieeexplore.ieee.org/document/9636213/ | [
"Ziqi Lu",
"Qiangqiang Huang",
"Kevin Doherty",
"John J. Leonard",
"Ziqi Lu",
"Qiangqiang Huang",
"Kevin Doherty",
"John J. Leonard"
] | Building object-level maps can facilitate robot-environment interactions (e.g. planning and manipulation), but objects could often have multiple probable poses when viewed from a single vantage point, due to symmetry, occlusion or perceptual failures. A robust object-level simultaneous localization and mapping (object SLAM) algorithm needs to be aware of this pose ambiguity. We propose to maintain... |
GR-Fusion: Multi-sensor Fusion SLAM for Ground Robots with High Robustness and Low Drift | https://ieeexplore.ieee.org/document/9636232/ | [
"Ting Wang",
"Yun Su",
"Shiliang Shao",
"Chen Yao",
"Zhidong Wang",
"Ting Wang",
"Yun Su",
"Shiliang Shao",
"Chen Yao",
"Zhidong Wang"
] | This paper presents a tightly coupled pipeline, which efficiently fuses measurements of LiDAR, camera, IMU, encoder, and GNSS to estimate the robot state and build a map even in challenging situations. The depth of visual features is extracted by projecting the LiDAR point cloud and ground plane into image. We select the tracked high-quality visual features and LiDAR features and tightly coupled t... |
Multi-layer VI-GNSS Global Positioning Framework with Numerical Solution aided MAP Initialization | https://ieeexplore.ieee.org/document/9636871/ | [
"Bing Han",
"Zhongyang Xiao",
"Shuai Huang",
"Tao Zhang",
"Bing Han",
"Zhongyang Xiao",
"Shuai Huang",
"Tao Zhang"
] | Motivated by the goal of achieving long-term drift-free camera pose estimation in complex scenarios, we propose a global positioning framework fusing visual, inertial and Global Navigation Satellite System (GNSS) measurements in multiple layers. Different from previous loosely- and tightly-coupled methods, the proposed multi-layer fusion allows us to delicately correct the drift of visual odometry... |
Angular Super-Resolution Radar SLAM | https://ieeexplore.ieee.org/document/9636438/ | [
"Zhiyuan Zeng",
"Xiangwei Dang",
"Yanlei Li",
"Xiangxi Bu",
"Xingdong Liang",
"Zhiyuan Zeng",
"Xiangwei Dang",
"Yanlei Li",
"Xiangxi Bu",
"Xingdong Liang"
] | Radar SLAM has attracted wide attention due to its all-day and all-weather working characteristics in the last decade. The existing radar SLAM systems mainly adopt mechanically pivoting radar with simple principle and high resolution, but this kind of radar has disadvantages such as low frame rate, distortion of the radar image, and high cost. Although array snapshot radar has the advantages of hi... |
CFEAR Radarodometry - Conservative Filtering for Efficient and Accurate Radar Odometry | https://ieeexplore.ieee.org/document/9636253/ | [
"Daniel Adolfsson",
"Martin Magnusson",
"Anas Alhashimi",
"Achim J. Lilienthal",
"Henrik Andreasson",
"Daniel Adolfsson",
"Martin Magnusson",
"Anas Alhashimi",
"Achim J. Lilienthal",
"Henrik Andreasson"
] | This paper presents an accurate, highly efficient and learning free method for large-scale radar odometry estimation. By using a simple filtering technique that keeps the strongest returns, we produce a clean radar data representation and reconstruct surface normals for efficient and accurate scan matching. Registration is carried out by minimizing a point-to-line metric and robustness to outliers... |
BSP-MonoLoc: Basic Semantic Primitives based Monocular Localization on Roads | https://ieeexplore.ieee.org/document/9636321/ | [
"Heping Li",
"Changliang Xue",
"Feng Wen",
"Hongbo Zhang",
"Wei Gao",
"Heping Li",
"Changliang Xue",
"Feng Wen",
"Hongbo Zhang",
"Wei Gao"
] | Robust visual localization in traffic scenes is a fundamental problem for self-driving vehicles. However, it is still challenging to achieve accurate localization performance because of drastic viewpoint and illumination changes. To address the issues, we design a novel monocular localization framework based on a light-weight prior map, called BSP-MonoLoc, which leverages the 2D semantic primitive... |
Ground Encoding: Learned Factor Graph-based Models for Localizing Ground Penetrating Radar | https://ieeexplore.ieee.org/document/9636764/ | [
"Alexander Baikovitz",
"Paloma Sodhi",
"Michael Dille",
"Michael Kaess",
"Alexander Baikovitz",
"Paloma Sodhi",
"Michael Dille",
"Michael Kaess"
] | We address the problem of robot localization using ground penetrating radar (GPR) sensors. Current approaches for localization with GPR sensors require a priori maps of the system’s environment as well as access to approximate global positioning (GPS) during operation. In this paper, we propose a novel, real-time GPR-based localization system for unknown and GPS-denied environments. We model the l... |
CLMM-Net: Robust Cascaded LiDAR Map Matching based on Multi-Level Intensity Map | https://ieeexplore.ieee.org/document/9636332/ | [
"Kai Chen",
"Lei He",
"Xiaofeng Wang",
"Yuqian Liu",
"Ming Zhao",
"Kai Chen",
"Lei He",
"Xiaofeng Wang",
"Yuqian Liu",
"Ming Zhao"
] | LiDAR map matching(LMM) is a critical localization technique in autonomous driving while existing methods have problems in terms of both accuracy and robustness when driving in the scenes with poor structure information (e.g. highways). This paper put forward a multi-level intensity map based cascaded network for LiDAR map matching in autonomous driving. The network uses an effective multi-level i... |
DLL: Direct LIDAR Localization. A map-based localization approach for aerial robots | https://ieeexplore.ieee.org/document/9636501/ | [
"Fernando Caballero",
"Luis Merino",
"Fernando Caballero",
"Luis Merino"
] | This paper presents DLL, a fast direct map-based localization technique using 3D LIDAR for its application to aerial robots. DLL implements a point cloud to map registration based on non-linear optimization of the distance of the points and the map, thus not requiring features, neither point correspondences. Given an initial pose, the method is able to track the pose of the robot by refining the p... |
Real-time Multi-Adaptive-Resolution-Surfel 6D LiDAR Odometry using Continuous-time Trajectory Optimization | https://ieeexplore.ieee.org/document/9636763/ | [
"Jan Quenzel",
"Sven Behnke",
"Jan Quenzel",
"Sven Behnke"
] | Simultaneous Localization and Mapping (SLAM) is an essential capability for autonomous robots, but due to high data rates of 3D LiDARs real-time SLAM is challenging. We propose a real-time method for 6D LiDAR odometry. Our approach combines a continuous-time B-Spline trajectory representation with a Gaussian Mixture Model (GMM) formulation to jointly align local multi-resolution surfel maps. Spars... |
Efficient Localisation Using Images and OpenStreetMaps | https://ieeexplore.ieee.org/document/9635972/ | [
"Mengjie Zhou",
"Xieyuanli Chen",
"Noe Samano",
"Cyrill Stachniss",
"Andrew Calway",
"Mengjie Zhou",
"Xieyuanli Chen",
"Noe Samano",
"Cyrill Stachniss",
"Andrew Calway"
] | The ability to localise is key for robot navigation. We describe an efficient method for vision-based localisation, which combines sequential Monte Carlo tracking with matching ground-level images to 2-D cartographic maps such as OpenStreetMaps. The matching is based on a learned embedded space representation linking images and map tiles, encoding the common semantic information present in both an... |
Interaction-Based Trajectory Prediction Over a Hybrid Traffic Graph | https://ieeexplore.ieee.org/document/9636143/ | [
"Sumit Kumar",
"Yiming Gu",
"Jerrick Hoang",
"Galen Clark Haynes",
"Micol Marchetti-Bowick",
"Sumit Kumar",
"Yiming Gu",
"Jerrick Hoang",
"Galen Clark Haynes",
"Micol Marchetti-Bowick"
] | Behavior prediction of traffic actors is an essential component of any real-world self-driving system. Actors’ long-term behaviors tend to be governed by their interactions with other actors or traffic elements (traffic lights, stop signs) in the scene. To capture this highly complex structure of interactions, we propose to use a hybrid graph whose nodes represent both the traffic actors as well a... |
Robust LiDAR Localization on an HD Vector Map without a Separate Localization Layer | https://ieeexplore.ieee.org/document/9636227/ | [
"Chi Zhang",
"Liwen Liu",
"Zhoupeng Xue",
"Kun Guo",
"Kuiyuan Yang",
"Rui Cai",
"Zhiwei Li",
"Chi Zhang",
"Liwen Liu",
"Zhoupeng Xue",
"Kun Guo",
"Kuiyuan Yang",
"Rui Cai",
"Zhiwei Li"
] | Many autonomous driving applications nowadays come along with a prebuilt vector map for routing and planning purposes. In order to localize on this map, traditional LiDAR localization methods usually require a separate localization layer to function. On one hand, the separate layer occupies large storage and is not convenient to update. On the other hand, the potential of the vector map itself has... |
AVP-Loc: Surround View Localization and Relocalization Based on HD Vector Map for Automated Valet Parking | https://ieeexplore.ieee.org/document/9636746/ | [
"Chi Zhang",
"Hao Liu",
"Zhijun Xie",
"Kuiyuan Yang",
"Kun Guo",
"Rui Cai",
"Zhiwei Li",
"Chi Zhang",
"Hao Liu",
"Zhijun Xie",
"Kuiyuan Yang",
"Kun Guo",
"Rui Cai",
"Zhiwei Li"
] | Localization is a crucial prerequisite for automated valet parking, in which a vehicle is required to navigate itself in a GPS-denied parking lot. Traditional visual localization methods usually build a feature map and use it for future localizations. However, the feature map is not robust to changes in illumination, appearance, and viewing perspective. To deal with this issue, we need a more stab... |
Map Compressibility Assessment for LiDAR Registration | https://ieeexplore.ieee.org/document/9636789/ | [
"Ming-Fang Chang",
"Wei Dong",
"Joshua Mangelson",
"Michael Kaess",
"Simon Lucey",
"Ming-Fang Chang",
"Wei Dong",
"Joshua Mangelson",
"Michael Kaess",
"Simon Lucey"
] | We aim to assess the performance of LiDAR-to-map registration on compressive maps. Modern autonomous vehicles utilize pre-built HD (High-Definition) maps to perform sensor-to-map registration, which recovers pose estimation failures and reduces drift in a large-scale environment. However, sensor-to-map registration is usually realized by registering the sensor to a dense 3D model, which occupies m... |
Subsets and Splits