A Study of Task-Space Path-Velocity Control for Torque-Limited Redundant Manipulators under Uncertainties

This paper addresses the time-optimal path-tracking problem for redundant manipulators. By integrating path-velocity control into existing task-space robot controllers, the task-space motion can be dynamically scaled to satisfy the torque constraint under both kinematic and dynamic uncertainties. Numerical simulations and experiments demonstrate that trajectory feasibility and path-tracking accuracy of the task-space controllers can be significantly improved by integrating path-velocity control. In addition, the nullspace motion of redundant manipulators can be exploited to further improve the performance by tracking the approximate time-optimal joint trajectory associated with the tasks in nullspace.

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Publication Details

Published
2025-06-24
DOI
https://doi.org/10.23919/ecc65951.2025.11187049
Primary Topic
Robotic Mechanisms and Dynamics
Type
article
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article

A Study of Task-Space Path-Velocity Control for Torque-Limited Redundant Manipulators under Uncertainties

Björn Olofsson, Yiannis Karayiannidis, Jia Zheng
Robotic Mechanisms and Dynamics
article

A Study of Task-Space Path-Velocity Control for Torque-Limited Redundant Manipulators under Uncertainties

Björn Olofsson, Yiannis Karayiannidis, Jia Zheng
article en

Abstract

This paper addresses the time-optimal path-tracking problem for redundant manipulators. By integrating path-velocity control into existing task-space robot controllers, the task-space motion can be dynamically scaled to satisfy the torque constraint under both kinematic and dynamic uncertainties. Numerical simulations and experiments demonstrate that trajectory feasibility and path-tracking accuracy of the task-space controllers can be significantly improved by integrating path-velocity control. In addition, the nullspace motion of redundant manipulators can be exploited to further improve the performance by tracking the approximate time-optimal joint trajectory associated with the tasks in nullspace.

Lund University (SE)
Openalex Percentile: Top 63%
Robotic Mechanisms and Dynamics
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