Trajectory optimization (TO) is an efficient tool to generate a redundant manipulator's joint trajectory following a 6-dimensional Cartesian path. The optimization performance largely depends on the quality of initial trajectories. However, the selection of a high-quality initial trajectory is non-trivial and requires a considerable time budget due to the extremely large space of the solution trajectories and the lack of prior knowledge about task constraints in configuration space. To alleviate the issue, we present a learning-based initial trajectory generation method that generates high-quality initial trajectories in a short time budget by adopting example-guided reinforcement learning. In addition, we suggest a null-space projected imitation reward to consider null-space constraints by efficiently learning kinematically feasible motion captured in expert demonstrations. Our statistical evaluation in simulation shows the improved optimality, efficiency, and applicability of TO when we plug in our method's output, compared with three other baselines. We also show the performance improvement and feasibility via real-world experiments with a seven-degree-of-freedom manipulator.
Optimal point-to-point trajectory planning for planar redundant manipulator is considered in this study. The main objective is to minimize the sum of the position error of the end-effector at each intermediate point along the trajectory so that the end-effector can track the prescribed trajectory accurately. An algorithm combining Genetic Algorithm and Pattern Search as a Generalized Pattern Search GPS is introduced to design the optimal trajectory. To verify the proposed algorithm, simulations for a 3-D-O-F planar manipulator with different end-effector trajectories have been carried out. A c…
A redundant manipulator has multiple inverse kinematics solutions per end-effector pose. Accordingly, there can be many trajectories for joints that follow a given endeffector path in the Cartesian space. In this paper, we present a trajectory optimization of a redundant manipulator (TORM) to synthesize a trajectory that follows a given end-effector path accurately, while achieving smoothness and collisionfree manipulation. Our method holistically incorporates three desired properties into the trajectory optimization process by integrating the Jacobian-based inverse kinematics solving method a…
Computer Science and Engineering Department, University of South Carolina（南卡罗来纳大学计算机科学与工程系）；Department of Mechanical Engineering, National Technical University of Athens（雅典国立技术大学机械工程系）
A hyper-redundant robotic arm is a manipulator with many degrees of freedom, capable of executing tasks in cluttered environments where robotic arms with fewer degrees of freedom are unable to operate. This paper introduces a new method for modeling those manipulators in a completely dynamic way. The proposed method enables online changes of the kinematic structure with the use of a special function; termed "meta-controlling function". This function can be used to develop policies to reduce drastically the computational cost for a single task, and to robustly control the robotic arm, even in t…
Dynamic Programming-Based Offline Redundancy Resolution of Redundant Manipulators Along Prescribed Paths with Real-Time Adjustment
School of Mathematical Sciences, Zhejiang University（浙江大学数学科学学院）；Zhejiang Demetics Medical Technology Co., Ltd.（浙江迪美特斯医疗科技有限公司）；Teachers College, Columbia University（哥伦比亚大学教师学院）；Zhejiang College of Sports（浙江体育学院）；Shenzhen Institute for Advanced Study, University of Electronic Science and Technology of China（电子科技大学深圳高等研究院）
TU Wien（维也纳工业大学）；University of Liverpool（利物浦大学）；Austrian Institute of Technology GmbH (AIT)（奥地利技术研究院有限公司）
Solving the analytical inverse kinematics (IK) of redundant manipulators in real time is a difficult problem in robotics since its solution for a given target pose is not unique. Moreover, choosing the optimal IK solution with respect to application-specific demands helps to improve the robustness and to increase the success rate when driving the manipulator from its current configuration towards a desired pose. This is necessary, especially in high-dynamic tasks like catching objects in mid-flights. To compute a suitable target configuration in the joint space for a given target pose in the t…
Dynamic Programming-Based Redundancy Resolution for Path Planning of Redundant Manipulators Considering Breakpoints
School of Mathematical Sciences, Zhejiang University（浙江大学数学科学学院）；Zhejiang Demetics Medical Technology Co., Ltd.（浙江德美特斯医疗科技有限公司）；Teachers College, Columbia University（哥伦比亚大学教师学院）；Zhejiang College of Sports（浙江体育学院）；Shenzhen Institute for Advanced Study, University of Electronic Science and Technology of China（电子科技大学深圳高等研究院）
Harbin Institute of Technology（哈尔滨工业大学）；University of Maryland at College Park（马里兰大学帕克分校）
We present a novel algorithm for collision-free kinematics of multiple manipulators in a shared workspace with moving obstacles. Our optimization-based approach simultaneously handles collision-free constraints based on reciprocal velocity obstacles and inverse kinematics constraints for high-DOF manipulators. We present an efficient method based on particle swarm optimization that can generate collision-free configurations for each redundant manipulator. Furthermore, our approach can be used to compute safe and oscillation-free trajectories in a few milli-seconds. We highlight the real-time p…
This paper presents a kinematic definition of a serialized Stewart platform designed for autonomous in-space assembly called an Assembler. The Assemblers architecture describes problems inherent to the inverse kinematics of over-actuated mixed kinematic systems. This paper also presents a methodology for optimizing poses. In order to accomplish this with the Assembler system, an algorithm for finding a feasible solution to its inverse kinematics was developed with a wrapper for a nonlinear optimization algorithm designed to minimize the magnitude of forces incurred by each actuator. A simulate…
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）
RobotDiffuse: Diffusion-Based Motion Planning for Redundant Manipulators with the ROP Obstacle Avoidance Dataset
School of Computer Science and Engineering, Beihang University, Beijing, China（北京航空航天大学计算机科学与工程学院）；School of Software, Beihang University, Beijing, China（北京航空航天大学软件学院）；Hangzhou Innovation Institute, Beihang University, Hangzhou, China（北京航空航天大学杭州创新研究院）
An internal model of the own body can be assumed a fundamental and evolutionary-early representation as it is present throughout the animal kingdom. Such functional models are, on the one hand, required in motor control, for example solving the inverse kinematic or dynamic task in goal-directed movements or a forward task in ballistic movements. On the other hand, such models are recruited in cognitive tasks as are planning ahead or observation of actions of a conspecific. Here, we present a functional internal body model that is based on the Mean of Multiple Computations principle. For the fi…
B*: Efficient and Optimal Base Placement for Fixed-Base Manipulators
Institute for Artificial Intelligence, Peking University（北京大学人工智能研究院）；School of Psychological and Cognitive Sciences, Peking University（北京大学心理与认知科学学院）；Beijing Key Laboratory of Behavior and Mental Health, Peking University（北京大学行为与心理健康北京重点实验室）；LeapZenith AI Research（LeapZenith人工智能研究）；University of Chinese Academy of Sciences（中国科学院大学）
Warm-Starting Optimization-Based Motion Planning for Robotic Manipulators via Point Cloud-Conditioned Flow Matching
J. Mike Walker ’66 Department of Mechanical Engineering, Texas A&M University（J. Mike Walker ’66 机械工程系，德克萨斯A&M大学）；Zachry Department of Civil and Environmental Engineering, Texas A&M University（Zachry 市政与环境工程系，德克萨斯A&M大学）
A Task-Driven, Planner-in-the-Loop Computational Design Framework for Modular Manipulators
Humanoids and Human Centered Mechatronics Research Line, Italian Institute of Technology (IIT) Genoa, Italy（意大利理工学院（IIT）热那亚人类与以人为中心的机电研究组）；Department of Industrial Engineering, University of Trento, Trento, Italy（特伦托大学工业工程系）
Multimodal Control of Manipulators: Coupling Kinematics and Vision for Self-Driving Laboratory Operations
1 Department of Electronics Systems, Aalborg University, Denmark；3 Extreme Robotics Laboratory, School of Metallurgy \& Materials, University of Birmingham, Birmingham, United Kingdom
Ecole Centrale de Lille（里尔中央理工学院）；Beihang University（北京航空航天大学）
A high redundant non-holonomic humanoid mobile dual-arm manipulator system is presented in this paper where the motion planning to realize "human-like" autonomous navigation and manipulation tasks is studied. Firstly, an improved MaxiMin NSGA-II algorithm, which optimizes five objective functions to solve the problems of singularity, redundancy, and coupling between mobile base and manipulator simultaneously, is proposed to design the optimal pose to manipulate the target object. Then, in order to link the initial pose and that optimal pose, an off-line motion planning algorithm is designed. I…
Real-Time Conformal-Seeded Hybrid Inverse Kinematics for Offset Redundant Manipulators
VinRobotics；Nanyang Technological University（南洋理工大学）；VinRobotics JSC（VinRobotics股份公司）；Center for AI Research (CAIR), VinUniversity（VinUniversity人工智能研究中心）
This paper presents an interconnected control-planning strategy for redundant manipulators, subject to system and environmental constraints. The method incorporates low-level control characteristics and high-level planning components into a robust strategy for manipulators acting in complex environments, subject to joint limits. This strategy is formulated using an adaptive control rule, the estimated dynamic model of the robotic system and the nullspace of the linearized constraints. A path is generated that takes into account the capabilities of the platform. The proposed method is computati…
Mainly because of the heavy computational costs, the real-time whole-body obstacle avoidance for the redundant manipulators has not been well implemented. This paper presents an approach that can ensure that the whole-body of a redundant manipulator can avoid moving obstacles in real-time during the execution of a task. The manipulator is divided into end-effector and non-end-effector portion. Based on dynamical systems (DS), the real-time end-effector obstacle avoidance is obtained. Besides, the end-effector can reach the given target. By using null-space velocity control, the real-time non-e…
Zhejiang University（浙江大学）；Shenzhen Sensetime Technology CO.,LTD（深圳商汤科技有限公司）；Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences（中国科学院深圳先进技术研究院）
Autonomous Underwater Vehicle-Manipulator systems (AUVMS) is a new tool for ocean exploration, the AUVMS path planning problem is addressed in this paper. AUVMS is a high dimension system with a large difference in inertia distribution, also it works in a complex environment with obstacles. By integrating the rapidly-exploring random tree(RRT) algorithm with the AUVMS kinematics model, the proposed RRTAUVMS algorithm could randomly sample in the configuration space(C-Space), and also grow the tree directly towards the workspace goal in the task space. The RRTAUVMS can also deal with the redund…
To economically deploy robotic manipulators the programming and execution of robot motions must be swift. To this end, we propose a novel, constraint-based method to intuitively specify sequential manipulation tasks and to compute time-optimal robot motions for such a task specification. Our approach follows the ideas of constraint-based task specification by aiming for a minimal and object-centric task description that is largely independent of the underlying robot kinematics. We transform this task description into a non-linear optimization problem. By solving this problem we obtain a (local…
University of South Carolina（南卡罗来纳大学）；United States Naval Academy（美国海军学院）
Despite the performance advantages of modern sampling-based motion planners, solving high dimensional planning problems in near real-time remains a challenge. Applications include hyper-redundant manipulators, snake-like and humanoid robots. Based on the intuition that many of these problem instances do not require the robots to exercise every degree of freedom independently, we introduce an enhancement to popular sampling-based planning algorithms aimed at circumventing the exponential dependence on dimensionality. We propose beginning the search in a lower dimensional subspace of the configu…
KU Leuven – University of Leuven（鲁汶大学）；University of Cambridge（剑桥大学）
This work addresses the inverse kinematics of serial robots using conformal geometric algebra. Classical approaches include either the use of homogeneous matrices, which entails high computational cost and execution time or the development of particular geometric strategies that cannot be generalized to arbitrary serial robots. In this work, we present a compact, elegant and intuitive formulation of robot kinematics based on conformal geometric algebra that provides a suitable framework for the closed-form resolution of the inverse kinematic problem for manipulators with a spherical wrist. For…
URPlanner: A Universal Paradigm For Collision-Free Robotic Motion Planning Based on Deep Reinforcement Learning
Integrative Sciences and Engineering Programme, NUS Graduate School, National University of Singapore（国家大学学院整合科学与工程计划）；Advanced Robotics Centre, National University of Singapore（国家大学新加坡先进机器人中心）；Department of Mechanical Engineering, College of Design and Engineering, National University of Singapore（设计与工程学院机械工程系）；Singapore MIT Alliance for Research and Technology (SMART) centre（新加坡MIT研究与技术联盟中心）
Robotic tasks, like reaching a pre-grasp configuration, are specified in the end effector space or task space, whereas, robot motion is controlled in joint space. Because of inherent actuation errors in joint space, robots cannot achieve desired configurations in task space exactly. Furthermore, different inverse kinematics (IK) solutions map joint space error set to task space differently. Thus for a given task with a prescribed error tolerance, all IK solutions will not be guaranteed to successfully execute the task. Any IK solution that is guaranteed to execute a task (possibly with high pr…
Sensor-Space Based Robust Kinematic Control of Redundant Soft Manipulator by Learning
Department of Mechanical and Aerospace Engineering, The University of Manchester, Manchester, United Kingdom（机械与航空航天工程系，曼彻斯特大学，英国曼彻斯特）；Department of Electrical and Electronic Engineering, The University of Manchester, Manchester, United Kingdom（电气与电子工程系，曼彻斯特大学，英国曼彻斯特）
Institut de Robòtica i Informàtica Industrial, CSIC-UPC（机器人与工业信息研究所（CSIC-UPC））；NASA-JPL, California Institute of Technology（美国国家航空航天局喷气推进实验室，加州理工学院）
Today's complex robotic designs comprise in some cases a large number of degrees of freedom, enabling for multi-objective task resolution (e.g., humanoid robots or aerial manipulators). This paper tackles the stability problem of a hierarchical losed-loop inverse kinematics algorithm for such highly redundant robots. We present a method to guarantee system stability by performing an online tuning of the closedloop control gains. We define a semi-definite programming problem (SDP) with these gains as decision variables and a discrete-time Lyapunov stability condition as a linear matrix inequali…
Recently, a time-varying quadratic programming (QP) framework that describes the tracking operations of redundant robot manipulators is introduced to handle the kinematic resolutions of many robot control tasks. Based on the generalization of such a time-varying QP framework, two schemes, i.e., the Repetitive Motion Scheme and the Hybrid Torque Scheme, are proposed. However, measurement noises are unavoidable when a redundant robot manipulator is executing a tracking task. To solve this problem, a novel integration-enhanced recurrent neural network (IE-RNN) is proposed in this paper. Associati…
Australian Centre for Field Robotics（澳大利亚现场机器人中心）；University of Sydney（悉尼大学）
This paper presents methods for finding optimal configurations and actuator forces/torques to maximise contact wrenches in a desired direction for Underwater Vehicles Manipulator Systems (UVMS). The wrench maximisation problem is formulated as a linear programming problem, and the optimal configuration is solved as a bi-level optimisation in the parameterised redundancy space. We additionally consider the cases of one or more manipulators with multiple contact forces, maximising wrench capability while tracking a trajectory, and generating large wrench impulses using dynamic motions. We look a…
We propose a novel design of a parallel manipulator of Stewart Gough type for virtual reality application of single individuals; i.e. an omni-directional treadmill is mounted on the motion platform in order to improve VR immersion by giving feedback to the human body. For this purpose we modify the well-known octahedral manipulator in a way that it has one degree of kinematical redundancy; namely an equiform reconfigurability of the base. The instantaneous kinematics and singularities of this mechanism are studied, where especially "unavoidable singularities" are characterized. These are poses…
