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Sim-to-Real Learning of Footstep-Constrained Bipedal Dynamic Walking | https://ieeexplore.ieee.org/document/9812015/ | [
"Helei Duan",
"Ashish Malik",
"Jeremy Dao",
"Aseem Saxena",
"Kevin Green",
"Jonah Siekmann",
"Alan Fern",
"Jonathan Hurst",
"Helei Duan",
"Ashish Malik",
"Jeremy Dao",
"Aseem Saxena",
"Kevin Green",
"Jonah Siekmann",
"Alan Fern",
"Jonathan Hurst"
] | Recently, work on reinforcement learning (RL) for bipedal robots has successfully learned controllers for a variety of dynamic gaits with robust sim-to-real demonstrations. In order to maintain balance, the learned controllers have full freedom of where to place the feet, resulting in highly robust gaits. In the real world however, the environment will often impose constraints on the feasible foot... |
Bipedal Walking on Constrained Footholds: Momentum Regulation via Vertical COM Control | https://ieeexplore.ieee.org/document/9812247/ | [
"Min Dai",
"Xiaobin Xiong",
"Aaron Ames",
"Min Dai",
"Xiaobin Xiong",
"Aaron Ames"
] | This paper presents an online walking synthesis methodology to enable dynamic and stable walking on constrained footholds for underactuated bipedal robots. Our approach modulates the change of angular momentum about the foot-ground contact pivot at discrete impact using pre-impact vertical center of mass (COM) velocity. To this end, we utilize the underactuated Linear Inverted Pendulum (LIP) model... |
Online Learning of Centroidal Angular Momentum towards Enhancing DCM-based Locomotion | https://ieeexplore.ieee.org/document/9811708/ | [
"Robert Schuller",
"George Mesesan",
"Johannes Englsberger",
"Jinoh Lee",
"Christian Ott",
"Robert Schuller",
"George Mesesan",
"Johannes Englsberger",
"Jinoh Lee",
"Christian Ott"
] | Gait generation frameworks for humanoid robots typically assume a constant centroidal angular momentum (CAM) throughout the walking cycle, which induces undesirable contact torques in the feet and results in performance degradation. In this work, we present a novel algorithm to learn the CAM online and include the obtained knowledge within the closed-form solutions of the Divergent Component of Mo... |
Sim-to-Real Learning for Bipedal Locomotion Under Unsensed Dynamic Loads | https://ieeexplore.ieee.org/document/9811783/ | [
"Jeremy Dao",
"Kevin Green",
"Helei Duan",
"Alan Fern",
"Jonathan Hurst",
"Jeremy Dao",
"Kevin Green",
"Helei Duan",
"Alan Fern",
"Jonathan Hurst"
] | Recent work on sim-to-real learning for bipedal locomotion has demonstrated new levels of robustness and agility over a variety of terrains. However, that work, and most prior bipedal locomotion work, have not considered locomotion under a variety of external loads that can significantly influence the overall system dynamics. In many applications, robots will need to maintain robust locomotion und... |
Bayesian Optimization Meets Hybrid Zero Dynamics: Safe Parameter Learning for Bipedal Locomotion Control | https://ieeexplore.ieee.org/document/9812154/ | [
"Lizhi Yang",
"Zhongyu Li",
"Jun Zeng",
"Koushil Sreenath",
"Lizhi Yang",
"Zhongyu Li",
"Jun Zeng",
"Koushil Sreenath"
] | In this paper, we propose a multi-domain control parameter learning framework that combines Bayesian Optimization (BO) and Hybrid Zero Dynamics (HZD) for locomotion control of bipedal robots. We leverage BO to learn the control parameters used in the HZD-based controller. The learning process is firstly deployed in simulation to optimize different control parameters for a large repertoire of gaits... |
A Benchmark Comparison of Learned Control Policies for Agile Quadrotor Flight | https://ieeexplore.ieee.org/document/9811564/ | [
"Elia Kaufmann",
"Leonard Bauersfeld",
"Davide Scaramuzza",
"Elia Kaufmann",
"Leonard Bauersfeld",
"Davide Scaramuzza"
] | Quadrotors are highly nonlinear dynamical systems that require carefully tuned controllers to be pushed to their physical limits. Recently, learning-based control policies have been proposed for quadrotors, as they would potentially allow learning direct mappings from high-dimensional raw sensory observations to actions. Due to sample inefficiency, training such learned controllers on the real pla... |
OSCAR: Data-Driven Operational Space Control for Adaptive and Robust Robot Manipulation | https://ieeexplore.ieee.org/document/9811967/ | [
"Josiah Wong",
"Viktor Makoviychuk",
"Anima Anandkumar",
"Yuke Zhu",
"Josiah Wong",
"Viktor Makoviychuk",
"Anima Anandkumar",
"Yuke Zhu"
] | Learning performant robot manipulation policies can be challenging due to high-dimensional continuous actions and complex physics-based dynamics. This can be alleviated through intelligent choice of action space. Operational Space Control (OSC) has been used as an effective task-space controller for manipulation. Nonetheless, its strength depends on the underlying modeling fidelity, and is prone t... |
Kinematics Learning of Massive Heterogeneous Serial Robots | https://ieeexplore.ieee.org/document/9812021/ | [
"Dengpeng Xing",
"Wannian Xia",
"Bo Xu",
"Dengpeng Xing",
"Wannian Xia",
"Bo Xu"
] | Kinematics and instantaneous kinematics are fundamental in many robotic tasks, such as positioning and collision avoidance. Existing learning methods mainly concern a single robot, and small-scale networks are sufficient for considerable approximation accuracy. A question is: Can we learn a kinematics model that can generalize to various robots rather than a single robot? This paper studies the ki... |
Integrating Deep Reinforcement and Supervised Learning to Expedite Indoor Mapping | https://ieeexplore.ieee.org/document/9811861/ | [
"Elchanan Zwecher",
"Eran Iceland",
"Sean R. Levy",
"Shmuel Y. Hayoun",
"Oren Gal",
"Ariel Barel",
"Elchanan Zwecher",
"Eran Iceland",
"Sean R. Levy",
"Shmuel Y. Hayoun",
"Oren Gal",
"Ariel Barel"
] | The challenge of mapping indoor environments is addressed. Typical heuristic algorithms for solving the motion planning problem are frontier-based methods, that are especially effective when the environment is completely unknown. However, in cases where prior statistical data on the environment's architectonic features is available, such algorithms can be far from optimal. Furthermore, their calcu... |
Learning to Optimize in Model Predictive Control | https://ieeexplore.ieee.org/document/9812369/ | [
"Jacob Sacks",
"Byron Boots",
"Jacob Sacks",
"Byron Boots"
] | Sampling-based Model Predictive Control (MPC) is a flexible control framework that can reason about non-smooth dynamics and cost functions. Recently, significant work has focused on the use of machine learning to improve the performance of MPC, often through learning or fine-tuning the dynamics or cost function. In contrast, we focus on learning to optimize more effectively. In other words, to imp... |
GPU-Accelerated Policy Optimization via Batch Automatic Differentiation of Gaussian Processes for Real-World Control | https://ieeexplore.ieee.org/document/9811876/ | [
"Abdolreza Taheri",
"Joni Pajarinen",
"Reza Ghabcheloo",
"Abdolreza Taheri",
"Joni Pajarinen",
"Reza Ghabcheloo"
] | The ability of Gaussian processes (GPs) to predict the behavior of dynamical systems as a more sample-efficient alternative to parametric models seems promising for real-world robotics research. However, the computational complexity of GPs has made policy search a highly time and memory consuming process that has not been able to scale to larger problems. In this work, we develop a policy optimiza... |
Next Steps: Learning a Disentangled Gait Representation for Versatile Quadruped Locomotion | https://ieeexplore.ieee.org/document/9811584/ | [
"Alexander L. Mitchell",
"Wolfgang Merkt",
"Mathieu Geisert",
"Siddhant Gangapurwala",
"Martin Engelcke",
"Oiwi Parker Jones",
"Ioannis Havoutis",
"Ingmar Posner",
"Alexander L. Mitchell",
"Wolfgang Merkt",
"Mathieu Geisert",
"Siddhant Gangapurwala",
"Martin Engelcke",
"Oiwi Parker Jones",
"Ioannis Havoutis",
"Ingmar Posner"
] | Quadruped locomotion is rapidly maturing to a degree where robots now routinely traverse a variety of unstructured terrains. However, while gaits can be varied typically by selecting from a range of pre-computed styles, current planners are unable to vary key gait parameters continuously while the robot is in motion. The synthesis, on-the-fly, of gaits with unexpected operational characteristics o... |
Targeted Attack on Deep RL-based Autonomous Driving with Learned Visual Patterns | https://ieeexplore.ieee.org/document/9811574/ | [
"Prasanth Buddareddygari",
"Travis Zhang",
"Yezhou Yang",
"Yi Ren",
"Prasanth Buddareddygari",
"Travis Zhang",
"Yezhou Yang",
"Yi Ren"
] | Recent studies demonstrated the vulnerability of control policies learned through deep reinforcement learning against adversarial attacks, raising concerns about the application of such models to risk-sensitive tasks such as autonomous driving. Threat models for these demonstrations are limited to (1) targeted attacks through real-time manipulation of the agent's observation, and (2) untargeted at... |
Forward Models That Integrate High-Dimensional and Localized Sensing of Peripheral Muscle Behavior Enable Task-Independent Prediction of Lower-Limb Joint Torque and Position Future States | https://ieeexplore.ieee.org/document/9812035/ | [
"Kaitlin G. Rabe",
"Nicholas P. Fey",
"Kaitlin G. Rabe",
"Nicholas P. Fey"
] | We develop a task-independent predictive framework that estimates hip, knee and ankle future behavior from sonomyographic sensing of quadriceps musculature. Two regression models, support vector regression and Gaussian process regression, were trained and tested such that no ambulation mode recognition was required. Sonomyography features of the anterior thigh musculature were extracted during the... |
TP-AE: Temporally Primed 6D Object Pose Tracking with Auto-Encoders | https://ieeexplore.ieee.org/document/9811890/ | [
"Linfang Zheng",
"Aleš Leonardis",
"Tze Ho Elden Tse",
"Nora Horanyi",
"Hua Chen",
"Wei Zhang",
"Hyung Jin Chang",
"Linfang Zheng",
"Aleš Leonardis",
"Tze Ho Elden Tse",
"Nora Horanyi",
"Hua Chen",
"Wei Zhang",
"Hyung Jin Chang"
] | Fast and accurate tracking of an object's motion is one of the key functionalities of a robotic system for achieving reliable interaction with the environment. This paper focuses on the instance-level six-dimensional (6D) pose tracking problem with a symmetric and textureless object under occlusion. We propose a Temporally Primed 6D pose tracking framework with Auto-Encoders (TP-AE) to tackle the ... |
Meta-confidence estimation for stereo matching | https://ieeexplore.ieee.org/document/9811620/ | [
"Seungryong Kim",
"Matteo Poggi",
"Sunok Kim",
"Kwanghoon Sohn",
"Stefano Mattoccia",
"Seungryong Kim",
"Matteo Poggi",
"Sunok Kim",
"Kwanghoon Sohn",
"Stefano Mattoccia"
] | We propose a novel framework to estimate the confidence of a disparity map taking into account, for the first time, the uncertainty affecting the confidence estimation process itself. Conversely to other tasks such as disparity estimation, the uncertainty of confidence directly hints that the confidence should be increased if initially low, but with high uncertainty, decreased otherwise. By modell... |
CenterSnap: Single-Shot Multi-Object 3D Shape Reconstruction and Categorical 6D Pose and Size Estimation | https://ieeexplore.ieee.org/document/9811799/ | [
"Muhammad Zubair Irshad",
"Thomas Kollar",
"Michael Laskey",
"Kevin Stone",
"Zsolt Kira",
"Muhammad Zubair Irshad",
"Thomas Kollar",
"Michael Laskey",
"Kevin Stone",
"Zsolt Kira"
] | This paper studies the complex task of simultaneous multi-object 3D reconstruction, 6D pose and size estimation from a single-view RGB-D observation. In contrast to instance- level pose estimation, we focus on a more challenging problem where CAD models are not available at inference time. Existing approaches mainly follow a complex multi-stage pipeline which first localizes and detects each objec... |
Flow Supervised Neural Radiance Fields for Static-Dynamic Decomposition | https://ieeexplore.ieee.org/document/9811680/ | [
"Quei-An Chen",
"Akihiro Tsukada",
"Quei-An Chen",
"Akihiro Tsukada"
] | We present an approach to synthesize novel views from dynamics scenes captured by multi-view videos of cameras mounted on a driving vehicle. We unify existing methods and propose a new training loss to explicitly disentangle the static background from the dynamic foreground objects using scene flow's magnitude, learnt only from proxy 2D optical flow supervision. We obtain high quality static and d... |
SAFIT: Segmentation-Aware Scene Flow with Improved Transformer | https://ieeexplore.ieee.org/document/9811747/ | [
"Yukang Shi",
"Kaisheng Ma",
"Yukang Shi",
"Kaisheng Ma"
] | Scene flow prediction is a challenging task that aims at jointly estimating the 3D structure and 3D motion of dynamic scenes. The previous methods concentrate more on point-wise estimation instead of considering the correspondence between objects as well as lacking the sensation of high-level semantic knowledge. In this paper, we propose a concise yet effective method for scene flow prediction. Th... |
AirLoop: Lifelong Loop Closure Detection | https://ieeexplore.ieee.org/document/9811658/ | [
"Dasong Gao",
"Chen Wang",
"Sebastian Scherer",
"Dasong Gao",
"Chen Wang",
"Sebastian Scherer"
] | Loop closure detection is an important building block that ensures the accuracy and robustness of simultaneous localization and mapping (SLAM) systems. Due to their generalization ability, CNN-based approaches have received increasing attention. Although they normally benefit from training on datasets that are diverse and reflective of the environments, new environments often emerge after the mode... |
R3LIVE: A Robust, Real-time, RGB-colored, LiDAR-Inertial-Visual tightly-coupled state Estimation and mapping package | https://ieeexplore.ieee.org/document/9811935/ | [
"Jiarong Lin",
"Fu Zhang",
"Jiarong Lin",
"Fu Zhang"
] | In this paper, we propose a novel LiDAR-Inertial-Visual sensor fusion framework termed R3LIVE, which takes advantage of measurement of LiDAR, inertial, and visual sensors to achieve robust and accurate state estimation. R3LIVE consists of two subsystems, a LiDAR-Inertial odometry (LIO) and a Visual-Inertial odometry (VIO). The LIO subsystem (FAST-LIO) utilizes the measurements from LiDAR and inert... |
Multi-Agent Path Finding with Prioritized Communication Learning | https://ieeexplore.ieee.org/document/9811643/ | [
"Wenhao Li",
"Hongjun Chen",
"Bo Jin",
"Wenzhe Tan",
"Hongyuan Zha",
"Xiangfeng Wang",
"Wenhao Li",
"Hongjun Chen",
"Bo Jin",
"Wenzhe Tan",
"Hongyuan Zha",
"Xiangfeng Wang"
] | Multi-agent pathfinding (MAPF) has been widely used to solve large-scale real-world problems, e.g., automation warehouses. The learning-based, fully decentralized framework has been introduced to alleviate real-time problems and simultaneously pursue optimal planning policy. However, existing methods might generate significantly more vertex conflicts (or collisions), which lead to a low success ra... |
Distributed Timed Elastic Band (DTEB) Planner: Trajectory Sharing and Collision Prediction for Multi-Robot Systems | https://ieeexplore.ieee.org/document/9811762/ | [
"Yiu Ming Chung",
"Hazem Youssef",
"Moritz Roidl",
"Yiu Ming Chung",
"Hazem Youssef",
"Moritz Roidl"
] | Autonomous navigation of mobile robots is a well-studied problem in robotics. However, the navigation task becomes challenging when multi-robot systems have to cooperatively navigate dynamic environments with deadlock-prone layouts. We present a Distributed Timed Elastic Band (DTEB) Planner that combines Prioritized Planning with the online TEB trajectory Planner, in order to extend the capabiliti... |
Optimizing Space Utilization for More Effective Multi-Robot Path Planning | https://ieeexplore.ieee.org/document/9812357/ | [
"Shuai D. Han",
"Jingjin Yu",
"Shuai D. Han",
"Jingjin Yu"
] | We perform a systematic exploration of the principle of Space Utilization Optimization (SUO) as a heuristic for planning better individual paths in a decoupled multi-robot path planner, with applications to both one-shot and life-long multi-robot path planning problems. We show that the heuristic set, SU - I, preserves single path optimality and significantly reduces congestion that naturally happ... |
Robust-by-Design Plans for Multi-Robot Pursuit-Evasion | https://ieeexplore.ieee.org/document/9812333/ | [
"Trevor Olsen",
"Nicholas M. Stiffler",
"Jason M. O'Kane",
"Trevor Olsen",
"Nicholas M. Stiffler",
"Jason M. O'Kane"
] | This paper studies a multi-robot visibility-based pursuit-evasion problem in which a group of pursuer robots are tasked with detecting an evader within a two dimensional polygonal environment. The primary contribution is a novel formulation of the pursuit-evasion problem that modifies the pursuers' objective by requiring that the evader still be de-tected, even in spite of the failure of any singl... |
Leveraging Smooth Attention Prior for Multi-Agent Trajectory Prediction | https://ieeexplore.ieee.org/document/9811718/ | [
"Zhangjie Cao",
"Erdem Biyik",
"Guy Rosman",
"Dorsa Sadigh",
"Zhangjie Cao",
"Erdem Biyik",
"Guy Rosman",
"Dorsa Sadigh"
] | Multi-agent interactions are important to model for forecasting other agents' behaviors and trajectories. At a certain time, to forecast a reasonable future trajectory, each agent needs to pay attention to the interactions with only a small group of most relevant agents instead of unnecessarily paying attention to all the other agents. However, existing attention modeling works ignore that human a... |
Optimal and Bounded-Suboptimal Multi-Goal Task Assignment and Path Finding | https://ieeexplore.ieee.org/document/9812020/ | [
"Xinyi Zhong",
"Jiaoyang Li",
"Sven Koenig",
"Hang Ma",
"Xinyi Zhong",
"Jiaoyang Li",
"Sven Koenig",
"Hang Ma"
] | We formalize and study the multi-goal task assignment and path finding (MG-TAPF) problem from theoretical and algorithmic perspectives. The MG-TAPF problem is to compute an assignment of tasks to agents, where each task consists of a sequence of goal locations, and collision-free paths for the agents that visit all goal locations of their assigned tasks in sequence. Theoretically, we prove that th... |
Fast and Optimal Trajectory Planning for Multiple Vehicles in a Nonconvex and Cluttered Environment: Benchmarks, Methodology, and Experiments | https://ieeexplore.ieee.org/document/9812126/ | [
"Yakun Ouyang",
"Bai Li",
"Youmin Zhang",
"Tankut Acarman",
"Yuqing Guo",
"Tantan Zhang",
"Yakun Ouyang",
"Bai Li",
"Youmin Zhang",
"Tankut Acarman",
"Yuqing Guo",
"Tantan Zhang"
] | This paper is focused on the cooperative trajectory planning problem for multiple car-like robots in a cluttered and unstructured environment narrowed by static obstacles. The concerned multi-vehicle trajectory planning (MVTP) problem is challenging because i) the scenario is nonconvex and tiny; ii) the vehicle kinematics is nonconvex; and iii) a feasible homotopy class is unavailable a priori. We... |
Prioritized Planning for Cooperative Range-Only Localization in Multi-Robot Networks | https://ieeexplore.ieee.org/document/9812315/ | [
"Alan Papalia",
"Nicole Thumma",
"John Leonard",
"Alan Papalia",
"Nicole Thumma",
"John Leonard"
] | We present a novel path-planning algorithm to reduce localization error for a network of robots cooperatively localizing via inter-robot range measurements. The quality of localization with range measurements depends on the configuration of the network, and poor configurations can cause substantial localization errors. To reduce the effect of network configuration on localization error for moving ... |
Multi-UAV Disaster Environment Coverage Planning with Limited-Endurance | https://ieeexplore.ieee.org/document/9812201/ | [
"Hongyu Song",
"Jincheng Yu",
"Jiantao Qiu",
"Zhixiao Sun",
"Kuijun Lang",
"Qing Luo",
"Yuan Shen",
"Yu Wang",
"Hongyu Song",
"Jincheng Yu",
"Jiantao Qiu",
"Zhixiao Sun",
"Kuijun Lang",
"Qing Luo",
"Yuan Shen",
"Yu Wang"
] | Disaster areas involving floods and earthquakes are commonly large, with the rescue time being quite tight, suggesting multi-Unmanned Aerial Vehicles (UAV) exploration rather than employing a single UAV. For such scenarios, current UAV exploration is modeled as a Coverage Path Planning (CPP) problem to achieve full area coverage in the presence of obstacles. However, the UAV's endurance capability... |
Load-sensitive Data Acquisition for a Tactile Sensor System of Multi-fingered Robotic Hands | https://ieeexplore.ieee.org/document/9812260/ | [
"Ryusuke Ishizaki",
"Shun Ogiwara",
"Fumiya Hamatsu",
"Tomoyuki Sakurai",
"Hirofumi Shin",
"Takahide Yoshiike",
"Ryusuke Ishizaki",
"Shun Ogiwara",
"Fumiya Hamatsu",
"Tomoyuki Sakurai",
"Hirofumi Shin",
"Takahide Yoshiike"
] | In this paper, we present a data acquisition method to realize a distributed tactile sensor system that can provide wide-range, and high-sensitivity with a small data size for communication. Since the data size is proportional to the number of acquired data and the resolution of the data, we propose systems to increase the resolution of the sensor output values without increasing the amount of dat... |
Design of a Biomimetic Tactile Sensor for Material Classification | https://ieeexplore.ieee.org/document/9811543/ | [
"Kevin Dai",
"Xinyu Wang",
"Allison M. Rojas",
"Evan Harber",
"Yu Tian",
"Nicholas Paiva",
"Joseph Gnehm",
"Evan Schindewolf",
"Howie Choset",
"Victoria A. Webster-Wood",
"Lu Li",
"Kevin Dai",
"Xinyu Wang",
"Allison M. Rojas",
"Evan Harber",
"Yu Tian",
"Nicholas Paiva",
"Joseph Gnehm",
"Evan Schindewolf",
"Howie Choset",
"Victoria A. Webster-Wood",
"Lu Li"
] | Tactile sensing typically involves active exploration of unknown surfaces and objects, making it especially effective at processing the characteristics of materials and textures. A key property extracted by human tactile perception in material classification is surface roughness, which relies on measuring vibratory signals using the multi-layered fingertip structure. Existing robotic systems lack ... |
GelSlim 3.0: High-Resolution Measurement of Shape, Force and Slip in a Compact Tactile-Sensing Finger | https://ieeexplore.ieee.org/document/9811832/ | [
"Ian H. Taylor",
"Siyuan Dong",
"Alberto Rodriguez",
"Ian H. Taylor",
"Siyuan Dong",
"Alberto Rodriguez"
] | This work presents a new version of tactile-sensing finger, GelSlim 3.0, which integrates the ability to sense high-resolution shape, force, and slip in a more compact form factor than previous implementations, designed for cluttered bin-picking scenarios. The novel design integrates real-time model-based algorithms to measure shape, estimate the 3-D contact force distribution, and detect incipien... |
Capacitive Tactile Sensor Using Mutual Capacitance Sensing Method for Increased Resolution | https://ieeexplore.ieee.org/document/9811696/ | [
"Jean-Christophe Sicotte-Brisson",
"Alexandre Bernier",
"Jennifer Kwiatkowski",
"Vincent Duchaine",
"Jean-Christophe Sicotte-Brisson",
"Alexandre Bernier",
"Jennifer Kwiatkowski",
"Vincent Duchaine"
] | As robots move toward more complex environments, imbuing them with a sense of touch similar to humans becomes increasingly important. To fulfill that goal, there has been significant research conducted in the past few decades to develop a tactile sensor that matches human level touch capabilities. Recently, the progress in capacitive touch screens has made capacitive sensing a very appealing optio... |
SpecTac: A Visual-Tactile Dual-Modality Sensor Using UV Illumination | https://ieeexplore.ieee.org/document/9812348/ | [
"Qi Wang",
"Yipai Du",
"Michael Yu Wang",
"Qi Wang",
"Yipai Du",
"Michael Yu Wang"
] | Perceiving the dynamical environment both visually and tactilely is crucial for the survival of animals, and therefore, is considered of importance in robotics research. Recently, there has been an increasing interest in vision-based tactile sensors due to their high sensing resolution and robustness to environmental changes. However, almost all vision-based tactile sensors make only partial use o... |
Parametric Path Optimization for Wheeled Robots Navigation | https://ieeexplore.ieee.org/document/9812167/ | [
"Zhiqiang Jian",
"Songyi Zhang",
"Jiahui Zhang",
"Shitao Chen",
"Nanning Zheng",
"Zhiqiang Jian",
"Songyi Zhang",
"Jiahui Zhang",
"Shitao Chen",
"Nanning Zheng"
] | Collision risk and smoothness are the most important factors in global path planning. Currently, planning methods that reduce global path collision risk and improve its smoothness through numerical optimization have achieved good results. However, these methods cannot always optimize the path. The reason is all points on the path are considered as decision variables, which leads to the high dimens... |
Autonomous Vehicle Parking in Dynamic Environments: An Integrated System with Prediction and Motion Planning | https://ieeexplore.ieee.org/document/9812309/ | [
"Jessica Leu",
"Yebin Wang",
"Masayoshi Tomizuka",
"Stefano Di Cairano",
"Jessica Leu",
"Yebin Wang",
"Masayoshi Tomizuka",
"Stefano Di Cairano"
] | This paper presents an integrated motion planning system for autonomous vehicle (AV) parking in the presence of other moving vehicles. The proposed system includes 1) a hybrid environment predictor that predicts the motions of the surrounding vehicles and 2) a strategic motion planner that reacts to the predictions. The hybrid environment predictor performs short-term predictions via an extended K... |
Smoothing Away From The Edge For Mesh Estimation in Urban Outdoor Environments | https://ieeexplore.ieee.org/document/9811563/ | [
"Jason Pilbrough",
"Paul Amayo",
"Jason Pilbrough",
"Paul Amayo"
] | 3D meshes offer a computationally efficient but still quite accurate path to the understanding of a robot's environment. While mesh reconstructions are often employed in indoor regions where regular planar surfaces dominate the scene, their use in urban outdoor environments has been under-explored. This is as outdoor urban environments produce a significant contrast between preserving discontinuit... |
Retriever: Point Cloud Retrieval in Compressed 3D Maps | https://ieeexplore.ieee.org/document/9811785/ | [
"Louis Wiesmann",
"Rodrigo Marcuzzi",
"Cyrill Stachniss",
"Jens Behley",
"Louis Wiesmann",
"Rodrigo Marcuzzi",
"Cyrill Stachniss",
"Jens Behley"
] | Most autonomous driving and robotic applications require retrieving map data around the vehicle's current location. Those maps can cover large areas and are often stored in a compressed form to save memory and allow for efficient transmission. In this paper, we address the problem of place recognition in a compressed point cloud map. To this end, we propose a novel deep neural network architecture... |
Design and Tests of a Novel Adjustable-stiffness Force Sensor | https://ieeexplore.ieee.org/document/9811826/ | [
"Xiantao Sun",
"Xiaoyu Xiong",
"Wenjie Chen",
"Yali Zhi",
"Weihai Chen",
"Yan Jin",
"Xiantao Sun",
"Xiaoyu Xiong",
"Wenjie Chen",
"Yali Zhi",
"Weihai Chen",
"Yan Jin"
] | In this paper, a novel adjustable-stiffness force sensor is developed for multitask measurements requiring different force resolutions and ranges. The applied force of the force sensor is indirectly measured through the linear deformation instead of the structure strain through an optical linear encoder. The main structure of the force sensor is actually a linear variable stiffness mechanism with ... |
A Low-Cost, Easy-to-Manufacture, Flexible, Multi-Taxel Tactile Sensor and its Application to In-Hand Object Recognition | https://ieeexplore.ieee.org/document/9811761/ | [
"Tessa J. Pannen",
"Steffen Puhlmann",
"Oliver Brock",
"Tessa J. Pannen",
"Steffen Puhlmann",
"Oliver Brock"
] | Soft robotics is an emerging field that yields promising results for tasks that require safe and robust interactions with the environment or with humans, such as grasping, manipulation, and human-robot interaction. Soft robots rely on intrinsically compliant components and are difficult to equip with traditional, rigid sensors which would interfere with their compliance. We propose a highly flexib... |
Soft-Jig: A Flexible Sensing Jig for Simultaneously Fixing and Estimating Orientation of Assembly Parts | https://ieeexplore.ieee.org/document/9812094/ | [
"Tatsuya Sakuma",
"Takuya Kiyokawa",
"Jun Takamatsu",
"Takahiro Wada",
"Tsukasa Ogasawara",
"Tatsuya Sakuma",
"Takuya Kiyokawa",
"Jun Takamatsu",
"Takahiro Wada",
"Tsukasa Ogasawara"
] | For assembly tasks, it is essential to fix target parts firmly and accurately estimate their poses. Several rigid jigs for individual parts are frequently used in assembly factories to achieve a precise and time-efficient product assembly. However, providing customized jigs is time-consuming. In this study, to address the lack of versatility in the shapes for which jigs can be used, we developed a... |
Expanding the Design Space for Electrically-Driven Soft Robots Through Handed Shearing Auxetics | https://ieeexplore.ieee.org/document/9812156/ | [
"Ian Good",
"Tosh Brown-Moore",
"Aditya Patil",
"Daniel Revier",
"Jeffrey Ian Lipton",
"Ian Good",
"Tosh Brown-Moore",
"Aditya Patil",
"Daniel Revier",
"Jeffrey Ian Lipton"
] | Handed Shearing Auxetics (HSA) are a promising structure for making electrically driven robots with distributed compliance that convert a motors rotation and torque into extension and force. These structures expand and contract by changing an internal angle between links, the evolution of the structure as this angle changes is known as the auxetic trajectory. We overcome past limitations on the ra... |
Multi-Dimensional Proprioception and Stiffness Tuning for Soft Robotic Joints | https://ieeexplore.ieee.org/document/9811555/ | [
"Zhonggui Fang",
"Chaoyi Huang",
"Yaxi Wang",
"Jiahao Xu",
"Jiyong Tan",
"Bin Li",
"Zichen Wang",
"Yige Wu",
"Anlun Huang",
"Juan Yi",
"Sicong Liu",
"Zheng Wang",
"Zhonggui Fang",
"Chaoyi Huang",
"Yaxi Wang",
"Jiahao Xu",
"Jiyong Tan",
"Bin Li",
"Zichen Wang",
"Yige Wu",
"Anlun Huang",
"Juan Yi",
"Sicong Liu",
"Zheng Wang"
] | Proprioception and variable stiffness are two trending topics in soft robotics research. The former could endow soft robots with the ability to perceive the environment as well as their internal states without the need of dedicated sensors, while the latter could strengthen the otherwise excessive compliance, enabling soft robots for tasks which require a higher force. Both directions have been ex... |
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