Shaping Impedances to Comply With Constrained Task Dynamics

Abstract

Humans are capable of managing multiple tasks simultaneously. It is widely assumed that human motor control can be emulated by impedance control. To achieve human-like behavior, however, the impedance parameters of multiple tasks may vary during task execution. We propose an algorithm that shapes task impedance as a function of the robot's time-varying inertial properties. These properties involve virtually constrained masses and virtually constrained inertias that counteract a task in order to comply with a given constraint. In this work, we not only detect task conflicts, but also show how to handle them. Our method is able to control kinematically redundant robots. We developed a dampingdesign method that does not interfere with our desired Cartesian task-space behavior. The control approach was verified in experiments on a real robot. We compared our impedance shaping method with two alternative control approaches: simple impedance superposition and nullspace projection. Our method preserved the passivity while improving the Cartesian task performance of an impedance controller. The method has computational advantages, beneficial to control robots with many degrees of freedom.

Learning to manipulate a whip with simple primitive actions – A simulation study

“…Prior research showed that impedance modulation was necessary to achieve complex manipulation tasks, e.g., managing physical interaction with the environment. 45 , 46 In fact, incorporating time-varying joint-space impedances into the controller could potentially broaden the range of targets that can be successfully hit by the whip, e.g., target 6. Investigating the potential advantages of variable joint-space impedances for complex object manipulation is a topic for future studies.…”

Design of an Energy-Aware Cartesian Impedance Controller for Collaborative Disassembly

“…The augmented energy tank described in [19] prevents the energy of the system from suddenly increasing within a single time step, thereby ensuring that the system stays stable. As mentioned in [27], the stored energy in an impedance-controlled robot can be expressed as a storage function S = S c + S r ∈ R, which is composed of the storage functions of the controller and the robot. S r is passive as the robot's energy is physically bounded from below [28].…”

Fractal impedance for passive controllers: a framework for interaction robotics

“…Their introduction into industries, such as health care, with complex interactive behaviour has revealed the limitations of traditional industrial controllers. The impedance controller [1][2][3][4][5][6] is a widespread technique enabling robots to interact with uncertain environments. This control technique relies on inverse dynamics modelling to drive the robot to act with a desired mechanical impedance, such as a linear Mass-Spring-Damper system [1,7].…”

“…Examples are environments that require adaptive trajectories and/or variable impedance gains [8], as well as tasks with uncertain end-effector contact against other agents or the environment (e.g., polishing, physical human-robot collaboration, etc.) [3][4][5][6][9][10][11][12][13]. Such tasks pose various challenges to robots' controllers that currently require an accurate model of contact conditions to ensure system stability.…”