This work presents the design and the corresponding stability analysis of desired model based, joint position constrained, robot controller. Specifically, provided that the initial joint position tracking error signal starts below some predefined value, the proposed controller ensures that the joint tracking error signal remains inside the region (defined by predefined upper--bound) and approaches to zero asymptotically.
Gravity Compensation of the dVRK-Si Patient Side Manipulator based on Dynamic Model Identification
Department of Robotics Engineering, Worcester Polytechnic Institute（机器人工程系，沃斯通理工大学）；Laboratory for Computational Sensing and Robotics, JHU（计算感知与机器人实验室，约翰·霍普金斯大学）；Department of Computer Science, Vanderbilt University（计算机科学系，范德比尔特大学）；Department of Computer Science, Johns Hopkins University（计算机科学系，约翰·霍普金斯大学）
This work presents the design and the corresponding stability analysis of a model based, joint position tracking error constrained, adaptive output feedback controller for robot manipulators. Specifically, provided that the initial joint position tracking error starts within a predefined region, the proposed controller algorithm ensures that the joint tracking error remains inside this region and asymptotically approaches to zero, despite the lack of joint velocity measurements and uncertainties associated with the system dynamics. The need for the joint velocity measurements are removed via t…
This manuscript introduces a passivity-based control methodology for fully-actuated mechanical systems with symmetric or asymmetric dead-zones. To this end, we find a smooth approximation of the inverse of the function that describes such a nonlinearity. Then, we propose an energy and damping injection approach - based on the PI-PBC technique - that compensates for the dead-zone. Moreover, we provide an analysis of the performance of the proposed controller near the equilibrium. We conclude this paper by experimentally validating the results on a two degrees-of-freedom planar manipulator.
University of Groningen（格罗宁根大学）；Universidad Complutense de Madrid（马德里康普顿斯大学）；Nanjing University of Science and Technology（南京理工大学）
We present three classes of distributed formation controllers for achieving and maintaining the 2D/3D formation shape of manipulator end-effectors to cope with different scenarios due to availability of modeling parameters. We firstly present a distributed formation controller for manipulators whose system parameters are perfectly known. The formation control objective is achieved by assigning virtual springs between end-effectors and by adding damping terms at joints, which provides a clear physical interpretation of the proposed solution. Subsequently, we extend it to the case where manipula…
This paper focuses on the construction of differential-cascaded structures for control of nonlinear robot manipulators subjected to disturbances and unavailability of partial information of the desired trajectory. The proposed differential-cascaded structures rely on infinite differential series to handle the robustness with respect to time-varying disturbances and the partial knowledge of the desired trajectories for nonlinear robot manipulators. The long-standing problem of reliable adaptation in the presence of sustaining disturbances is solved by the proposed forwardstepping control with f…
Closed-Loop Control and Disturbance Mitigation of an Underwater Multi-Segment Continuum Manipulator
National Robotarium（国家机器人研究院）；Heriot Watt University（赫瑞瓦特大学）；Institute for Integrated Micro and Nano Systems（集成微纳系统研究所）；University of Edinburgh（爱丁堡大学）；Senai Cimatec（塞奈伊·西马泰克）；CREATE Lab（CREATE实验室）；EPFL（洛桑联邦理工学院）
This paper is concerned with the optimal kinematic control of a robot manipulator where the robot end effector position follows a task space trajectory. The joints are actuated with the desired velocity profile to achieve this task. This problem has been solved using a single network adaptive critic (SNAC) by expressing the forward kinematics as input affine system. Usually in SNAC, the critic weights are updated using back propagation algorithm while little attention is given to convergence to the optimal cost. In this paper, we propose a critic weight update law that ensures convergence to t…
Quadrupedal manipulators require to be compliant when dealing with external forces during autonomous manipulation, tele-operation or physical human-robot interaction. This paper presents a whole-body controller that allows for the implementation of a Cartesian impedance control to coordinate tracking performance and desired compliance for the robot base and manipulator arm. The controller is formulated through an optimization problem using Quadratic Programming (QP) to impose a desired behavior for the system while satisfying friction cone constraints, unilateral force constraints, joint and t…
Soft robots are robotic systems made of deformable materials and exhibit unique flexibility that can be exploited for complex environments and tasks. However, their control problem has been considered a challenging subject because they are of infinite degrees of freedom and highly under-actuated. Existing studies have mainly relied on simplified and approximated finite-dimensional models. In this work, we exploit infinite-dimensional nonlinear control for soft robots. We adopt the Cosserat-rod theory and employ nonlinear partial differential equations (PDEs) to model the kinematics and dynamic…
Electro-hydraulic servo-systems are widely employed in industrial applications such as robotic manipulators, active suspensions, precision machine tools and aerospace systems. They provide many advantages over electric motors, including high force to weight ratio, fast response time and compact size. However, precise control of electro-hydraulic systems, due to their inherent nonlinear characteristics, cannot be easily obtained with conventional linear controllers. Most flow control valves can also exhibit some hard nonlinearities such as dead-zone due to valve spool overlap. This work describ…
In this paper an artificial delay based impedance controller is proposed for robotic manipulators with uncertainty in dynamics. The control law unites the time delayed estimation (TDE) framework with a second order switching controller of super twisting algorithm (STA) type via a novel generalized filtered tracking error (GFTE). While time delayed estimation framework eliminates the need for accurate modelling of robot dynamics by estimating the uncertain robot dynamics and interaction forces from immediate past data of state and control effort, the second order switching control law in the ou…
Institute of Robotics and Mechatronics of the German Aerospace Center (DLR)（德国航空航天中心（DLR）机器人与机电一体化研究所）；Department of Electrical Engineering, COPPE, Federal University of Rio de Janeiro (UFRJ)（里约热内卢联邦大学（UFRJ）COPPE电气工程系）
When, in addition to stability, position synchronization is also desired in bilateral teleoperation, Time Domain Passivity Approach (TDPA) alone might not be able to fulfill the desired objective. This is due to an undesired effect caused by admittance type passivity controllers, namely position drift. Previous works focused on developing TDPA-based drift compensation methods to solve this issue. It was shown that, in addition to reducing drift, one of the proposed methods was able to keep the force signals within their normal range, guaranteeing the safety of the task. However, no multi-DoF t…
Shanghai Jiao Tong University（上海交通大学）；University of Oxford（牛津大学）；Tencent Robotics X Lab（腾讯机器人X实验室）
Designing safety-critical control for robotic manipulators is challenging, especially in a cluttered environment. First, the actual trajectory of a manipulator might deviate from the planned one due to the complex collision environments and non-trivial dynamics, leading to collision; Second, the feasible space for the manipulator is hard to obtain since the explicit distance functions between collision meshes are unknown. By analyzing the relationship between the safe set and the controlled invariant set, this paper proposes a data-driven control barrier function (CBF) construction method, whi…
In order to avoid conventional controlling methods which created obstacles due to the complexity of systems and intense demand on data density, developing modern and more efficient control methods are required. In this way, reinforcement learning off-policy and model-free algorithms help to avoid working with complex models. In terms of speed and accuracy, they become prominent methods because the algorithms use their past experience to learn the optimal policies. In this study, three reinforcement learning algorithms; DDPG, TD3 and SAC have been used to train Fetch robotic manipulator for fou…
Computing forward statics from tendon-length in flexible-joint hyper-redundant manipulators
Institute for Integrated Micro and Nano Systems, School of Engineering, University of Edinburgh（整合微纳系统研究所，工程学院，爱丁堡大学）；CREATE Lab, EPFL（EPFL CREATE 实验室）；Institute for Imaging, Data and Communications, School of Engineering, University of Edinburgh（成像、数据与通信研究所，工程学院，爱丁堡大学）
Adaptive Gravity Compensation Control of a Cable-Driven Upper-Arm Soft Exosuit
Birla Institute of Technology and Science Pilani（皮拉尼贝拉理工学院）；PricewaterhouseCoopers（普华永道）；Indian Institute of Technology Delhi（印度理工学院德里分校）；All India Institute of Medical Sciences（全印医学科学学院）
Purdue Polytechnic Institute, Purdue University（普渡大学普渡理工学院）；School of Engineering Technology, Purdue Polytechnic Institute, Purdue University（普渡大学普渡理工学院工程技术学院）；Purdue University（普渡大学）
Inspection for structural properties (surface stiffness and coefficient of restitution) is crucial for understanding and performing aerial manipulations in unknown environments, with little to no prior knowledge on their state. Inspection-on-the-fly is the uncanny ability of humans to infer states during manipulation, reducing the necessity to perform inspection and manipulation separately. This paper presents an infrastructure for inspection-on-the-fly method for aerial manipulators using hybrid physical interaction control. With the proposed method, structural properties (surface stiffness a…
Neural Network Aided Kalman Filtering with Model Predictive Control Enables Robot-Assisted Drone Recovery on a Wavy Surface
School of Data Science, The Chinese University of Hong Kong, Shenzhen, China（数据科学学院，香港中文大学（深圳））；School of Science and Engineering, The Chinese University of Hong Kong, Shenzhen, China（科学与工程学院，香港中文大学（深圳））；Shenzhen Institute of Artificial Intelligence and Robotics for Society, Shenzhen, China（社会人工智能与机器人研究所，深圳）
Data-driven Control with Real-time Uncertainty Compensation for Multi-Fuel Engines
Department of Mechanical Engineering, University of Minnesota Twin Cities（明尼苏达大学双城分校机械工程系）；DEVCOM Army Research Laboratory, Aberdeen Proving Ground, MD, USA（美国陆军研发实验室，阿伯丁试验场，马里兰州）
This work presents a solution to the adaptive tracking control of Euler Lagrange systems with guaranteed tracking and parameter estimation error convergence. Specifically a concurrent learning based update rule fused by the filtered version of the desired system dynamics in conjunction with a desired state based regression matrix has been utilized to ensure that both the position tracking error and parameter estimation error terms converge to origin exponentially. As the regression matrix used in proposed controller makes use of the desired versions of the system states, an initial, sufficient…
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…
