A Stability Analysis for the Acceleration-based Robust Position Control of Robot Manipulators via Disturbance Observer

This paper proposes a new nonlinear stability analysis for the acceleration-based robust position control of robot manipulators by using Disturbance Observer (DOb). It is shown that if the nominal inertia matrix is properly tuned in the design of DOb, then the position error asymptotically goes to zero in regulation control and is uniformly ultimately bounded in trajectory tracking control. As the bandwidth of DOb and the nominal inertia matrix are increased, the bound of error shrinks, i.e., the robust stability and performance of the position control system are improved. However, neither the bandwidth of DOb nor the nominal inertia matrix can be freely increased due to practical design constraints, e.g., the robust position controller becomes more noise sensitive when they are increased. The proposed stability analysis provides insights regarding the dynamic behavior of DOb-based robust motion control systems. It is theoretically and experimentally proved that non-diagonal elements of the nominal inertia matrix are useful to improve the stability and adjust the trade-off between the robustness and noise sensitivity. The validity of the proposal is verified by simulation and experimental results.Comment: 9 pages, 9 figures, Journa

Chapter 35: Free Simulation Software and Library

International audienceWith the advent of powerful computation technologies and efficient algorithms , simulators became an important tool in most engineering areas. The field of humanoid robotics is no exception; there have been numerous simulation tools developed over the last two decades to foster research and development activities. With this in mind, this chapter is written to introduce and discuss the current-day open source simulators that are actively used in the field. Using a developer-based feedback, we provide an outline regarding the specific features and capabilities of the open-source simulators, with a special emphasis on how they correspond to recent research trends in humanoid robotics. The discussion is centered around the contemporary requirements in humanoid simulation technologies with regards to future of the field

A Soft+Rigid Hybrid Exoskeleton Concept in Scissors-Pendulum Mode: A Suit for Human State Sensing and an Exoskeleton for Assistance

In this paper, we present a novel concept that can enable the human aware control of exoskeletons through the integration of a soft suit and a robotic exoskeleton. Unlike the state-of-the-art exoskeleton controllers which mostly rely on lumped human-robot models, the proposed concept makes use of the independent state measurements concerning the human user and the robot. The ability to observe the human state independently is the key factor in this approach. In order to realize such a system from the hardware point of view, we propose a system integration frame that combines a soft suit for human state measurement and a rigid exoskeleton for human assistance. We identify the technological requirements that are necessary for the realization of such a system with a particular emphasis on soft suit integration. We also propose a template model, named scissor pendulum, that may encapsulate the dominant dynamics of the human-robot combined model to synthesize a controller for human state regulation. A series of simulation experiments were conducted to check the controller performance. As a result, satisfactory human state regulation was attained, adequately confirming that the proposed system could potentially improve exoskeleton-aided applications

A Closed-form Analytical Solution to Torque Free Precession: Euler-Poinsot Problem

This work aims to disclose a closed-form analytical solution to attitude motion for a rigid body subject to zero body-fixed torques, i.e., Euler-Poinsot problem. Revisiting Routh’s study, the presence of multiple solutions are identified. To verify the proposed solution, numerical simulations and real-life experiment results are presented. A Code Ocean repository is also provided so that readers could test the algorithm individually.</p

A comparison study on observer-based force control of series elastic actuators

This paper presents a comparison study for the robust force control of series elastic actuators (SEAs). In most robotics systems, SEAs are used as an essential actuation method due to the benefits such as lower reflected inertia and safety. However, the robustness to the modeling uncertainties and external disturbances is still a study material for researchers. It is known that when model-based control methods are used with disturbance observers, high precision tracking results can be obtained. Therefore, in this study, model predictive control and model-based feedforward control methods are investigated in different scenarios and simulation results are provided for comparison

Challenges for the Policy Representation when Applying Reinforcement Learning in Robotics

Abstract—A summary of the state-of-the-art reinforcement learning in robotics is given, in terms of both algorithms and policy representations. Numerous challenges faced by the policy representation in robotics are identified. Two recent examples for application of reinforcement learning to robots are described: pancake flipping task and bipedal walking energy minimization task. In both examples, a state-of-the-art Expectation-Maximization-based reinforcement learning algorithm is used, but different policy representations are proposed and evaluated for each task. The two proposed policy representations offer viable solutions to four rarely-addressed challenges in policy representations: correlations, adaptability, multi-resolution, and globality. Both the successes and the practical difficulties encountered in these examples are discussed. I

A Stability Analysis for the Acceleration-based Robust Position Control of Robot Manipulators via Disturbance Observer

This paper proposes a new nonlinear stability analysis for the acceleration-based robust position control of robot manipulators by using Disturbance Observer (DOb). It is shown that if the nominal inertia matrix is properly tuned in the design of DOb, then the position error asymptotically goes to zero in regulation control and is uniformly ultimately bounded in trajectory tracking control. As the bandwidth of DOb and the nominal inertia matrix are increased, the bound of error shrinks, i.e., the robust stability and performance of the position control system are improved. However, neither the bandwidth of DOb nor the nominal inertia matrix can be freely increased due to practical design constraints, e.g., the robust position controller becomes more noise sensitive when they are increased. The proposed stability analysis provides insights regarding the dynamic behavior of DOb-based robust motion control systems. It is theoretically and experimentally proved that non-diagonal elements of the nominal inertia matrix are useful to improve the stability and adjust the trade-off between the robustness and noise sensitivity. The validity of the proposal is verified by simulation and experimental results

Active Compliance Control Reduces Upper Body Effort in Exoskeleton-Supported Walking

IEEE This article presents a locomotion controller for lower limb exoskeletons so as to enable the combined robot and user system to exhibit compliant walking characteristics when interacting with the environment. This is of critical importance to reduce the excessive ground reaction forces during the walking task execution with the aim of improved environmental interaction capabilities. In robot-aided walking support for paraplegics, the user has to actively use his/her upper limbs via crutches to ensure overall balance. By virtue of this requisite, several issues may particularly arise during touchdown instants, e.g., upper body orientation fluctuates, shoulder joints are subject to excessive loading, and arms may need to exert extra forces to counterbalance these effects. In order to reduce the upper body effort via compliant locomotion, the controller is designed to manage the force/position tradeoff by using an admittance controller in each joint. For proof of concept, a series of exoskeleton-aided walking experiments were conducted with the participation of nine healthy volunteers, four of whom additionally walked on an irregular surface for further performance evaluation. The results suggest that the proposed locomotion controller is advantageous over conventional high-gain position tracking in decreasing undesired oscillatory torso motion and total arm force, adequately reducing the required upper body effort