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MANIPULATION

Refined Post-Impact Velocity Prediction for Torque-Controlled Flexible-Joint Robots

Camilo Andres Rey Arias, Wouter Weekers, Marco Morganti, Vincent Padois, Alessandro Saccon

Year
2024
Citations
6

Abstract

Predicting the post-impact velocity for torque-controlled flexible-joint robots enhances impact-aware control schemes which exploit intentional collisions for achieving dynamic robotic manipulation and locomotion. Compared to a previous approach based on a fully rigid-robot assumption, this paper shows how an improvement in the post-impact velocity prediction can be obtained by taking into account the joints' motor inertias, transmission ratios, and low-level torque control gains, as well as the impact surface friction. The letter also proposes a more robust method to estimate the gross post-impact velocity profile from experimental data via a polynomial fit. The improvement of the new post-impact velocity prediction is illustrated by means of both numerical simulations as well as 50 experimental trials on a commercially available torque-controlled robot. The recorded impact data and prediction algorithms are shared openly for reproducibility and further research.

Keywords

TorqueRobotExploitControl theory (sociology)Computer scienceJoint (building)SimulationControl (management)EngineeringArtificial intelligence

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