Haptic upper limb exoskeletons are robots that assist human operators during task execution while having the ability to render virtual or remote environments. Therefore, the stability of such robots in physical human-robot-environment interaction must be guaranteed, in addition to performing well during task execution. Having a wide range of Z-width, which shows the region of passively renderable impedance by a haptic display, is also important to render a wide range of virtual environments. To address these issues, in this study, subsystem-based adaptive impedance control is designed for having a stable human-robot-environment interaction of 7 degrees of freedom haptic exoskeleton. The presented control decomposes the entire system into subsystems and designs the controller at the subsystem level. The stability of the controller in the presence of contact with the virtual environment and human arm force is proved by employing the virtual stability concept. Additionally, the Z-width of the 7-DoF haptic exoskeleton is drawn using experimental data and improved using varying virtual mass element for the virtual environment. Finally, experimental results are provided to demonstrate the perfect performance of the proposed controller in accomplishing the predefined task.
Variable impedance control in operation-space is a promising approach to learning contact-rich manipulation behaviors. One of the main challenges with this approach is producing a manipulation behavior that ensures the safety of the arm and the environment. Such behavior is typically implemented via a reward function that penalizes unsafe actions (e.g. obstacle collision, joint limit extension), but that approach is not always effective and does not result in behaviors that can be reused in slightly different environments. We show how to combine Riemannian Motion Policies, a class of policies …
Agile Robots AG（敏捷机器人公司）；Fraunhofer IPK（弗劳恩霍夫生产设备与设计技术研究所）；Universität Hamburg（汉堡大学）；Intel Asia-Pacific Research & Development Ltd.（英特尔亚太研发有限公司）
Dynamic movement primitives (DMPs) allow complex position trajectories to be efficiently demonstrated to a robot. In contact-rich tasks, where position trajectories alone may not be safe or robust over variation in contact geometry, DMPs have been extended to include force trajectories. However, different task phases or degrees of freedom may require the tracking of either position or force -- e.g., once contact is made, it may be more important to track the force demonstration trajectory in the contact direction. The robot impedance balances between following a position or force reference tra…
University of Groningen（格罗宁根大学）；University of Bologna（博洛尼亚大学）
This work is devoted to an impedance grasping strategy for a class of standard mechanical systems in the port-Hamiltonian framework. We embed a variable rest-length of the springs of the existing impedance grasping strategy in order to achieve a stable non-contact to contact transition, and a desired grasping force. We utilize the port-Hamiltonian structure of standard mechanical systems. First, we utilize a change of variables that transforms the port-Hamiltonian system into one with a constant mass-inertia matrix. We then achieve impedance grasping control via a \emph{virtual spring} with a …
Using large datasets in machine learning has led to outstanding results, in some cases outperforming humans in tasks that were believed impossible for machines. However, achieving human-level performance when dealing with physically interactive tasks, e.g., in contact-rich robotic manipulation, is still a big challenge. It is well known that regulating the Cartesian impedance for such operations is of utmost importance for their successful execution. Approaches like reinforcement Learning (RL) can be a promising paradigm for solving such problems. More precisely, approaches that use task-agnos…
PRISMA Lab, Department of Electrical Engineering and Information Technology, University of Naples Federico II（那不勒斯费德里科二世大学电气工程与信息技术系PRISMA实验室）；Chair of Information-oriented Control (ITR), Department of Electrical and Computer Engineering, Technical University of Munich（慕尼黑工业大学电气与计算机工程系信息导向控制教席）
Tandon School of Engineering, New York University（纽约大学坦登工程学院）；Max Planck Institute for Intelligent Systems（马克斯·普朗克智能系统研究所）
This paper addresses the problem of computing optimal impedance schedules for legged locomotion tasks involving complex contact interactions. We formulate the problem of impedance regulation as a trade-off between disturbance rejection and measurement uncertainty. We extend a stochastic optimal control algorithm known as Risk Sensitive Control to take into account measurement uncertainty and propose a formal way to include such uncertainty for unknown contact locations. The approach can efficiently generate optimal state and control trajectories along with local feedback control gains, i.e. im…
CompliantVLA-adaptor: VLM-Guided Variable Impedance Action for Safe Contact-Rich Manipulation
Human-Robot Interfaces and Interaction Lab, Istituto Italiano di Tecnologia, Genoa, Italy（人机交互实验室，意大利理工学院，热那亚，意大利）；Ph.D. program of national interest in Robotics and Intelligent Machines (DRIM) and Università di Genova, Genoa, Italy（机器人与智能机器国家利益博士项目和热那亚大学，热那亚，意大利）；Edwardson School of Industrial Engineering, Purdue University, West Lafayette, IN 47907, USA（工业工程埃德华森学校，普渡大学，西拉法克萨，印第安纳州47907，美国）；Georgia Institute of Technology, Atlanta, USA（佐治亚理工学院，亚特兰大，美国）；German Research Center for AI, Germany（德国人工智能研究中心，德国）；TU Darmstadt, Darmstadt, Germany（图宾根大学，图宾根，德国）；Karlsruhe Institute of Technology, Karlsruhe, Germany（卡尔斯鲁厄理工学院，卡尔斯鲁厄，德国）
Max-Planck Institute for Intelligent Systems（马克斯·普朗克智能系统研究所）；New York University（纽约大学）
Reinforcement learning algorithms have shown great success in solving different problems ranging from playing video games to robotics. However, they struggle to solve delicate robotic problems, especially those involving contact interactions. Though in principle a policy directly outputting joint torques should be able to learn to perform these tasks, in practice we see that it has difficulty to robustly solve the problem without any given structure in the action space. In this paper, we investigate how the choice of action space can give robust performance in presence of contact uncertainties…
Visuo-Tactile Exploration of Unknown Rigid 3D Curvatures by Vision-Augmented Unified Force-Impedance Control
Chair of Robotics and Systems Intelligence, MIRMI-Munich Institute of Robotics and Machine Intelligence, Technical University of Munich（慕尼黑工业大学机器人与系统智能教席，慕尼黑机器人与机器智能研究所）；Centre for Tactile Internet with Human-in-the-Loop (CeTI)（以人为中心的触觉互联网中心）
Diffusion-Based Impedance Learning for Contact-Rich Manipulation Tasks
Institute for Anthropomatics and Robotics, Karlsruhe Institute of Technology（人机动力学与机器人研究所，卡尔斯鲁厄技术大学）；Department of Mechanical Engineering, Massachusetts Institute of Technology（机械工程系，麻省理工学院）；Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology（脑与认知科学系，麻省理工学院）
Reinforcement Learning (RL) of contact-rich manipulation tasks has yielded impressive results in recent years. While many studies in RL focus on varying the observation space or reward model, few efforts focused on the choice of action space (e.g. joint or end-effector space, position, velocity, etc.). However, studies in robot motion control indicate that choosing an action space that conforms to the characteristics of the task can simplify exploration and improve robustness to disturbances. This paper studies the effect of different action spaces in deep RL and advocates for Variable Impedan…
OmniVIC: A Self-Improving Variable Impedance Controller with Vision-Language In-Context Learning for Safe Robotic Manipulation
Human-Robot Interfaces and Interaction Lab, Istituto Italiano di Tecnologia, Genoa, Italy（人机交互实验室，意大利理工学院，热那亚）；Georgia Institute of Technology, Atlanta, USA（佐治亚理工学院，美国亚特兰大）
Assistive robots for healthcare have seen a growing demand due to the great potential of relieving medical practitioners from routine jobs. In this paper, we investigate the development of an optimization-based control framework for an ultrasound-guided assistive robot to perform scoliosis assessment. A conventional procedure for scoliosis assessment with ultrasound imaging typically requires a medical practitioner to slide an ultrasound probe along a patient's back. To automate this type of procedure, we need to consider multiple objectives, such as contact force, position, orientation, energ…
University of California, Berkeley（加州大学伯克利分校）；Harbin Institute of Technology（哈尔滨工业大学）
Many manipulation tasks require robots to interact with unknown environments. In such applications, the ability to adapt the impedance according to different task phases and environment constraints is crucial for safety and performance. Although many approaches based on deep reinforcement learning (RL) and learning from demonstration (LfD) have been proposed to obtain variable impedance skills on contact-rich manipulation tasks, these skills are typically task-specific and could be sensitive to changes in task settings. This paper proposes an inverse reinforcement learning (IRL) based approach…
Royal Institute of Technology（瑞典皇家理工学院）；ASEA Brown Boveri (ABB) Corporate Research（ABB集团企业研究院）
Reinforcement learning (RL) has had its fair share of success in contact-rich manipulation tasks but it still lags behind in benefiting from advances in robot control theory such as impedance control and stability guarantees. Recently, the concept of variable impedance control (VIC) was adopted into RL with encouraging results. However, the more important issue of stability remains unaddressed. To clarify the challenge in stable RL, we introduce the term all-the-time-stability that unambiguously means that every possible rollout will be stability certified. Our contribution is a model-free RL …
University of Edinburgh（爱丁堡大学）；University of Oxford（牛津大学）
Haptic interaction is essential for the dynamic dexterity of animals, which seamlessly switch from an impedance to an admittance behaviour using the force feedback from their proprioception. However, this ability is extremely challenging to reproduce in robots, especially when dealing with complex interaction dynamics, distributed contacts, and contact switching. Current model-based controllers require accurate interaction modelling to account for contacts and stabilise the interaction. In this manuscript, we propose an adaptive force/position controller that exploits the fractal impedance con…
Plug, Play and Comply: Plugin-Based Compliant Control in ROS 2
College of Information Science and Technology, Eastern Institute of Technology（信息科学与技术学院，东方理工学院）；Zhejiang Key Laboratory of Industrial Intelligence and Digital Twin, Eastern Institute of Technology（浙江省工业智能与数字孪生重点实验室，东方理工学院）
Max Planck Institute for Intelligent Systems（马克斯·普朗克智能系统研究所）；Tandon School of Engineering, New York University（纽约大学坦登工程学院）；Laboratory for Analysis and Architecture of Systems, Centre National pour la Recherche Scientifique（法国国家科学研究中心系统分析与架构实验室）
We present a new open-source torque-controlled legged robot system, with a low-cost and low-complexity actuator module at its core. It consists of a high-torque brushless DC motor and a low-gear-ratio transmission suitable for impedance and force control. We also present a novel foot contact sensor suitable for legged locomotion with hard impacts. A 2.2 kg quadruped robot with a large range of motion is assembled from eight identical actuator modules and four lower legs with foot contact sensors. Leveraging standard plastic 3D printing and off-the-shelf parts results in a lightweight and inexp…
Soft robotic systems offer benefits over traditional rigid systems through reduced contact trauma with soft tissues and by enabling access through tortuous paths in minimally invasive surgery. However, the inherent deformability of soft robots places both a greater onus on accurate modelling of their shape, and greater challenges in realising intraoperative shape sensing. Herein we present a proprioceptive (self-sensing) soft actuator, with an electrically conductive working fluid. Electrical impedance measurements from up to six electrodes enabled tomographic reconstructions using Electrical …
Robust Adaptive Backstepping Impedance Control of Robots in Unknown Environments
Research Center for Systems and Technologies (SYSTEC), ARISE, Faculty of Engineering, University of Porto, 4200-465 Porto, Portugal（系统与技术研究中心（SYSTEC），ARISE，工程学院，波尔图大学，葡萄牙4200-465波尔图）；Intelligent Autonomous Systems Lab, Department of Computer Science, TU Darmstadt, Germany（智能自主系统实验室，计算机科学系，达姆施塔特技术大学，德国）
Sunrise Setting Ltd（日出设置有限公司）；SAGE Publications Ltd（SAGE出版有限公司）；University of Birmingham（伯明翰大学）；Honda Research Institute Europe GmbH（本田欧洲研究院有限公司）
We describe a framework for changing-contact robot manipulation tasks that 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, and the highly non-linear nature of the dynamics during contact changes can be damaging to the robot and the objects. We present an adaptive control framework that enables the robot to incrementally learn to predict contact changes in a changing contact task, learn the interaction dynamics of the piece-wise continu…
Fraunhofer Institute for Production Systems and Design Technology（弗劳恩霍夫生产系统与设计技术研究所）
Force control enables hands-on teaching and physical collaboration, with the potential to improve ergonomics and flexibility of automation. Established methods for the design of compliance, impedance control, and \rev{collision response} can achieve free-space stability and acceptable peak contact force on lightweight, lower payload robots. Scaling collaboration to higher payloads can allow new applications, but introduces challenges due to the more significant payload dynamics and the use of higher-payload industrial robots. To achieve high-payload manual guidance with contact, this paper pro…
