Energy budgets for coordinate invariant robot control in physical human–robot interaction

Abstract

In this work we consider the current certification process of applications with physical human–robot interaction (pHRI). Two major hazards are collisions and clamping scenarios. The implementation of safety measures in pHRI applications typically depends strongly on coordinates, e.g., to monitor the robot velocity or to predict external forces. We show that the current certification process does not, in general, guarantee a safe robot behavior. In particular, in unstructured environments it is not possible to predict all risks in advance. We therefore propose to control the energy of the robot, which is a coordinate invariant entity. For an impedance controlled robot, the total energy consists of potential energy and kinetic energy. The energy flow from task description to physical interaction follows a strict causality. We assign a safe energy budget for the robot. With this energy budget, the presented controller auto-tunes its parameters to limit the exchanged kinetic energy during a collision and the potential energy during clamping scenarios. In contact, the robot behaves compliantly and therefore eliminates clamping danger. After contact, the robot automatically continues to follow the desired trajectory. With this approach the number of safety-related parameters to be determined can be reduced to one energy value, which has the potential to significantly speed up the commissioning of pHRI applications. The proposed technique is validated by experiments.

Using Physics-Based Digital Twins and Extended Reality for the Safety and Ergonomics Evaluation of Cobotic Workstations

“…A collision between a body part and a robot link may be modelled as a linear spring-damper system with a stiffness k depending on the impacted body part (Vemula et al, 2018) (Svarný et al, 2020) (Ferraguti et al, 2020). A simple relationship may then be established between the impact force F and the transferred energy E (Lachner et al, 2021) (see Equation 3), involving the robot's effective mass. Force limits given by the ISO/TS 15 066 can then be transcribed into velocity and energy limits, which can be easier to interpret or compute.…”

A General Framework for Hierarchical Redundancy Resolution Under Arbitrary Constraints

“…However, joint velocity minimization has been shown to have drawbacks for robots whose joint coordinates present mixed units, which is often the case when considering robots with a large number of DOFs, e.g., mobile manipulators [30]. This aspect is also essential in the context of energy-aware motion generation [31]. Therefore, a proper redundancy resolution algorithm should provide the possibility to select more appropriate metrics.…”

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.…”