Robot Impedance Control and Passivity Analysis with Inner Torque and Velocity Feedback Loops

Impedance control is a well-established technique to control interaction forces in robotics. However, real implementations of impedance control with an inner loop may suffer from several limitations. Although common practice in designing nested control systems is to maximize the bandwidth of the inner loop to improve tracking performance, it may not be the most suitable approach when a certain range of impedance parameters has to be rendered. In particular, it turns out that the viable range of stable stiffness and damping values can be strongly affected by the bandwidth of the inner control loops (e.g. a torque loop) as well as by the filtering and sampling frequency. This paper provides an extensive analysis on how these aspects influence the stability region of impedance parameters as well as the passivity of the system. This will be supported by both simulations and experimental data. Moreover, a methodology for designing joint impedance controllers based on an inner torque loop and a positive velocity feedback loop will be presented. The goal of the velocity feedback is to increase (given the constraints to preserve stability) the bandwidth of the torque loop without the need of a complex controller.Comment: 14 pages in Control Theory and Technology (2016

A shared position/force control methodology for teleoperation

A flexible and computationally efficient shared position/force control concept and its implementation in the Robot Control C Library (RCCL) are presented form the point of teleoperation. This methodology enables certain degrees of freedom to be position-controlled through real time manual inputs and the remaining degrees of freedom to be force-controlled by computer. Functionally, it is a hybrid control scheme in that certain degrees of freedom are designated to be under position control, and the remaining degrees of freedom to be under force control. However, the methodology is also a shared control scheme because some degrees of freedom can be put under manual control and the other degrees of freedom put under computer control. Unlike other hybrid control schemes, which process position and force commands independently, this scheme provides a force control loop built on top of a position control inner loop. This feature minimizes the computational burden and increases disturbance rejection. A simple implementation is achieved partly because the joint control servos that are part of most robots can be used to provide the position control inner loop. Along with this control scheme, several menus were implemented for the convenience of the user. The implemented control scheme was successfully demonstrated for the tasks of hinged-panel opening and peg-in-hole insertion

Force/torque and tactile sensors for sensor-based manipulator control

The autonomy of manipulators, in space and in industrial environments, can be dramatically enhanced by the use of force/torque and tactile sensors. The development and future use of a six-component force/torque sensor for the Hermes Robot Arm (HERA) Basic End-Effector (BEE) is discussed. Then a multifunctional gripper system based on tactile sensors is described. The basic transducing element of the sensor is a sheet of pressure-sensitive polymer. Tactile image processing algorithms for slip detection, object position estimation, and object recognition are described

Benchmarking Cerebellar Control

Cerebellar models have long been advocated as viable models for robot dynamics control. Building on an increasing insight in and knowledge of the biological cerebellum, many models have been greatly refined, of which some computational models have emerged with useful properties with respect to robot dynamics control. Looking at the application side, however, there is a totally different picture. Not only is there not one robot on the market which uses anything remotely connected with cerebellar control, but even in research labs most testbeds for cerebellar models are restricted to toy problems. Such applications hardly ever exceed the complexity of a 2 DoF simulated robot arm; a task which is hardly representative for the field of robotics, or relates to realistic applications. In order to bring the amalgamation of the two fields forwards, we advocate the use of a set of robotics benchmarks, on which existing and new computational cerebellar models can be comparatively tested. It is clear that the traditional approach to solve robotics dynamics loses ground with the advancing complexity of robotic structures; there is a desire for adaptive methods which can compete as traditional control methods do for traditional robots. In this paper we try to lay down the successes and problems in the fields of cerebellar modelling as well as robot dynamics control. By analyzing the common ground, a set of benchmarks is suggested which may serve as typical robot applications for cerebellar models

Balancing experiments on a torque-controlled humanoid with hierarchical inverse dynamics

Recently several hierarchical inverse dynamics controllers based on cascades of quadratic programs have been proposed for application on torque controlled robots. They have important theoretical benefits but have never been implemented on a torque controlled robot where model inaccuracies and real-time computation requirements can be problematic. In this contribution we present an experimental evaluation of these algorithms in the context of balance control for a humanoid robot. The presented experiments demonstrate the applicability of the approach under real robot conditions (i.e. model uncertainty, estimation errors, etc). We propose a simplification of the optimization problem that allows us to decrease computation time enough to implement it in a fast torque control loop. We implement a momentum-based balance controller which shows robust performance in face of unknown disturbances, even when the robot is standing on only one foot. In a second experiment, a tracking task is evaluated to demonstrate the performance of the controller with more complicated hierarchies. Our results show that hierarchical inverse dynamics controllers can be used for feedback control of humanoid robots and that momentum-based balance control can be efficiently implemented on a real robot.Comment: appears in IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 201