Planning a motion for inserting pegs remains an open problem. The difficulty lies in both the inevitable errors in the grasps of a robotic hand and absolute precision problems in robot joint motors. This paper proposes an integral method to solve the problem. The method uses combined task and motion planning to plan the grasps and motion for a dual-arm robot to pick up the objects and move them to assembly poses. Then, it controls the dual-arm robot using a compliant strategy (a combination of linear search, spiral search, and impedance control) to finish up the insertion. The method is implemented on a dual-arm Universal Robots 3 robot. Six objects, including a connector with fifteen peg-in-hole pairs for detailed analysis and other five objects with different contours of pegs and holes for additional validation, were tested by the robot. Experimental results show reasonable force-torque signal changes and end-effector position changes. The proposed method exhibits high robustness and high fidelity in successfully conducting planned peg-in-hole tasks.
We present a trajectory planning and control architecture for bipedal locomotion at a variety of speeds on a highly underactuated and compliant bipedal robot. A library of compliant walking trajectories are planned offline, and stored as compact arrays of polynomial coefficients for tracking online. The control implementation uses a floating-base inverse dynamics controller which generates dynamically consistent feedforward torques to realize walking using information obtained from the trajectory optimization. The effectiveness of the controller is demonstrated in simulation and on hardware fo…
Admittance-Based Motion Planning with Vision-Guided Initialization for Robotic Manipulators in Self-Driving Laboratories
Department of Electronics Systems, Aalborg University（电子系统系，奥尔堡大学）；Department of Information Technology and Electrical Engineering, Università degli Studi di Napoli Federico II（信息科技与电气工程系，那不勒斯费迪里奇二世大学）
Many robots operating in unpredictable environments require an online path planning algorithm that can quickly compute high quality paths. Asymptotically optimal planners are capable of finding the optimal path, but can be slow to converge. Local optimisation algorithms are capable of quickly improving a solution, but are not guaranteed to converge to the optimal solution. In this paper we develop a new way to integrate an asymptotically optimal planners with a local optimiser. We test our approach using RRTConnect* with a short-cutting local optimiser. Our approach results in a significant pe…
Zhejiang University（浙江大学）；Huzhou Institute of Zhejiang University（浙江大学湖州研究院）；The University of Hong Kong（香港大学）
For real-time multirotor kinodynamic motion planning, the efficiency of sampling-based methods is usually hindered by difficult-to-sample homotopy classes like narrow passages. In this paper, we address this issue by a hybrid scheme. We firstly propose a fast regional optimizer exploiting the information of local environments and then integrate it into a global sampling process to ensure faster convergence. The incorporation of local optimization on different sampling-based methods shows significantly improved success rates and less planning time in various types of challenging environments. W…
Max Planck Institute for Intelligent Systems（马克斯·普朗克智能系统研究所）；University of Tehran（德黑兰大学）；Tarbiat Modares University（塔比阿特莫达勒斯大学）；Hakim Sabzevari University（哈基姆萨卜泽瓦尔大学）；Sharif University of Technology（谢里夫理工大学）
Contact modeling plays a central role in motion planning, simulation, and control of legged robots, as legged locomotion is realized through contact. The two prevailing approaches to model the contact consider rigid and compliant premise at interaction ports. Contrary to the dynamics model of legged systems with rigid contact (without impact) which is straightforward to develop, there is no consensus among researchers to employ a standard compliant contact model. Our main goal in this paper is to study the dynamics model structure of bipedal walking systems with a rigid contact and a \textit{n…
Northeastern University（东北大学）；United States Coast Guard（美国海岸警卫队）；MIT - WHOI Joint Program（麻省理工学院-伍兹霍尔海洋研究所联合项目）；Lilium GmbH（莉莉姆公司）
In this paper, we look at the role of autonomous navigation in the maritime domain. Specifically, we examine how an Autonomous Surface Vessel(ASV) can achieve obstacle avoidance based on the Convention on the International Regulations for Preventing Collisions at Sea (1972), or COLREGs, in real-world environments. Our ASV is equipped with a broadband marine radar, an Inertial Navigation System (INS), and uses official Electronic Navigational Charts (ENC). These sensors are used to provide situational awareness and, in series of well-defined steps, we can exclude land objects from the radar dat…
Toward Integrating Semantic-aware Path Planning and Reliable Localization for UAV Operations
School of Information Science, Japan Advanced Institute of Science and Technology（日本先进科学技术学院信息科学部）；University of Engineering and Technology, Vietnam National University Hanoi（越南国家大学河内工程技术大学）
In unstructured urban canals, regulation-aware interactions with other vessels are essential for collision avoidance and social compliance. In this paper, we propose a regulations aware motion planning framework for Autonomous Surface Vessels (ASVs) that accounts for dynamic and static obstacles. Our method builds upon local model predictive contouring control (LMPCC) to generate motion plans satisfying kino-dynamic and collision constraints in real-time while including regulation awareness. To incorporate regulations in the planning stage, we propose a cost function encouraging compliance wit…
An enhanced motion planning approach by integrating driving heterogeneity and long-term trajectory prediction for automated driving systems
School of Transportation and Logistics, Southwest Jiaotong University（西南交通大学交通运输与物流学院）；University of Central Florida（中佛罗里达大学）；Lyles School of Civil Engineering, Purdue University（普渡大学莱尔土木工程学院）
Both pedestrian and robot comfort are of the highest priority whenever a robot is placed in an environment containing human beings. In the case of pedestrian-unaware mobile robots this desire for safety leads to the freezing robot problem, where a robot confronted with a large dynamic group of obstacles (such as a crowd of pedestrians) would determine all forward navigation unsafe causing the robot to stop in place. In order to navigate in a socially compliant manner while avoiding the freezing robot problem we are interested in understanding the flow of pedestrians in crowded scenarios. By tr…
Integrating path-planning and control for robotic unicycles
Department of Mechanical Engineering, University of Michigan（机械工程系，密歇根大学）；HUN-REN–BME Dynamics of Machines Research Group（HUN-REN–BME 机械动力学研究组）；Department of Mechanical Engineering and with the Department of Civil and Environmental Engineering, University of Michigan（机械工程系和土木与环境工程系，密歇根大学）；Department of Applied Mechanics, Budapest University of Technology and Economics（应用力学系，布达佩斯技术与经济大学）
Versatile, Robust, and Explosive Locomotion with Rigid and Articulated Compliant Quadrupeds
Cognitive Robotics, Delft University of Technology（代尔夫特理工大学认知机器人学系）；University of Trento（特伦托大学）；University of Manchester（曼彻斯特大学）；Institute of Robotics and Mechatronics, German Aerospace Center (DLR)（德国航空航天中心机器人与机电一体化研究所）
Siemens Corporate Technology（西门子中央研究院）；University of Freiburg（弗莱堡大学）
In automated manufacturing, robots must reliably assemble parts of various geometries and low tolerances. Ideally, they plan the required motions autonomously. This poses a substantial challenge due to high-dimensional state spaces and non-linear contact-dynamics. Furthermore, object poses and model parameters, such as friction, are not exactly known and a source of uncertainty. The method proposed in this paper models the task of parts assembly as a belief space planning problem over an underlying impedance-controlled, compliant system. To solve this planning problem we introduce an asymptoti…
Washington University in St. Louis（圣路易斯华盛顿大学）；Duke University（杜克大学）；Stevens Institute of Technology（史蒂文斯理工学院）；University of Michigan（密歇根大学）；Northeastern University（东北大学）
SAP-CoPE: Social-Aware Planning using Cooperative Pose Estimation with Infrastructure Sensor Nodes
Mechanical and Mechatronics Eng. Department, University of Waterloo（机械与机电工程系，滑铁库大学）；Department of Data and Systems Engineering, University of Hong Kong（数据与系统工程系，香港大学）；Mechanical Engineering Department, University of Alberta（机械工程系，阿尔伯塔大学）
University of Stuttgart（斯图加特大学）；Max Planck Institute for Intelligent Systems（马克斯·普朗克智能系统研究所）
Integrating robotic systems in architectural and construction processes is of core interest to increase the efficiency of the building industry. Automated planning for such systems enables design analysis tools and facilitates faster design iteration cycles for designers and engineers. However, generic task-and-motion planning (TAMP) for long-horizon construction processes is beyond the capabilities of current approaches. In this paper, we develop a multi-agent TAMP framework for long horizon problems such as constructing a full-scale building. To this end we extend the Logic-Geometric Program…
University of California, Berkeley（加州大学伯克利分校）；Carnegie Mellon University（卡内基梅隆大学）
Planning under social interactions with other agents is an essential problem for autonomous driving. As the actions of the autonomous vehicle in the interactions affect and are also affected by other agents, autonomous vehicles need to efficiently infer the reaction of the other agents. Most existing approaches formulate the problem as a generalized Nash equilibrium problem solved by optimization-based methods. However, they demand too much computational resource and easily fall into the local minimum due to the non-convexity. Monte Carlo Tree Search (MCTS) successfully tackles such issues in …
VLMPlanner: Integrating Visual Language Models with Motion Planning
University of Science and Technology of China（科学技术大学）；University of Adelaide（阿德莱德大学）；Institute of Artificial Intelligence, Hefei Comprehensive National Science Center（合肥综合性国家科学中心人工智能研究院）
PIE: Perception and Interaction Enhanced End-to-End Motion Planning for Autonomous Driving
Department of Mechanical Engineering, National University of Singapore（机械工程系，国立新加坡大学）；Department of Civil and Environmental Engineering, National University of Singapore（土木与环境工程系，国立新加坡大学）
Task-motion planning (TMP) addresses the problem of efficiently generating executable and low-cost task plans in a discrete space such that the (initially unknown) action costs are determined by motion plans in a corresponding continuous space. However, a task-motion plan can be sensitive to unexpected domain uncertainty and changes, leading to suboptimal behaviors or execution failures. In this paper, we propose a novel framework, TMP-RL, which is an integration of TMP and reinforcement learning (RL) from the execution experience, to solve the problem of robust task-motion planning in dynamic…
Istituto Italiano di Tecnologia（意大利技术研究院）；University of Edinburgh（爱丁堡大学）；University of Oxford（牛津大学）
Planning whole-body motions while taking into account the terrain conditions is a challenging problem for legged robots since the terrain model might produce many local minima. Our coupled planning method uses stochastic and derivatives-free search to plan both foothold locations and horizontal motions due to the local minima produced by the terrain model. It jointly optimizes body motion, step duration and foothold selection, and it models the terrain as a cost-map. Due to the novel attitude planning method, the horizontal motion plans can be applied to various terrain conditions. The attitud…
Highly constrained manipulation tasks continue to be challenging for autonomous robots as they require high levels of precision, typically less than 1mm, which is often incompatible with what can be achieved by traditional perception systems. This paper demonstrates that the combination of state-of-the-art object tracking with passively adaptive mechanical hardware can be leveraged to complete precision manipulation tasks with tight, industrially-relevant tolerances (0.25mm). The proposed control method closes the loop through vision by tracking the relative 6D pose of objects in the relevant …
Hybrid Terrain-Aware Path Planning: Integrating VD-RRT* Exploration and VD-D* Lite Repair
The Grainger College of Engineering, Electrical and Computer Engineering Department, University of Illinois Urbana-Champaign（伊利诺伊大学厄巴纳-香槟分校格拉inger工程学院）；The Grainger College of Engineering, Industrial and Enterprise Systems Engineering Department, University of Illinois Urbana-Champaign（伊利诺伊大学厄巴纳-香槟分校格拉inger工程学院）
University of Genoa（热那亚大学）；Arizona State University（亚利桑那州立大学）
We present an integrated Task-Motion Planning framework for robot navigation in belief space. Autonomous robots operating in real world complex scenarios require planning in the discrete (task) space and the continuous (motion) space. To this end, we propose a framework for integrating belief space reasoning within a hybrid task planner. The expressive power of PDDL+ combined with heuristic-driven semantic attachments performs the propagated and posterior belief estimates while planning. The underlying methodology for the development of the combined hybrid planner is discussed, providing sugge…
Real-Time Communication-Aware Ride-Sharing Route Planning for Urban Air Mobility: A Multi-Source Hybrid Attention Reinforcement Learning Approach
School of Science and Engineering, The Chinese University of Hong Kong, Shenzhen（科学与工程学院，香港中文大学（深圳））；Xidian University State Key Laboratory of Integrated Services Network（西安电子科技大学集成服务网络国家重点实验室）；Department of Computer Science and Engineering, Kyung Hee University（庆北大学计算机科学与工程系）
Regulation-Aware Game-Theoretic Motion Planning for Autonomous Racing
University of Modena and Reggio Emilia（摩德纳和雷吉奥艾米利亚大学）；University of Bologna（博洛尼亚大学）；University of California, Berkeley（加州大学伯克利分校）；Chalmers University of Technology（查尔姆斯理工大学）
Massachusetts Institute of Technology（麻省理工学院）；IBM Thomas J. Watson Research Center（IBM托马斯·J·沃森研究中心）
For robotic vehicles to navigate safely and efficiently in pedestrian-rich environments, it is important to model subtle human behaviors and navigation rules (e.g., passing on the right). However, while instinctive to humans, socially compliant navigation is still difficult to quantify due to the stochasticity in people's behaviors. Existing works are mostly focused on using feature-matching techniques to describe and imitate human paths, but often do not generalize well since the feature values can vary from person to person, and even run to run. This work notes that while it is challenging t…
The problem of planning for a robot that operates in environments containing a large number of objects, taking actions to move itself through the world as well as to change the state of the objects, is known as task and motion planning (TAMP). TAMP problems contain elements of discrete task planning, discrete-continuous mathematical programming, and continuous motion planning, and thus cannot be effectively addressed by any of these fields directly. In this paper, we define a class of TAMP problems and survey algorithms for solving them, characterizing the solution methods in terms of their st…
