Energy-Aware Hierarchical Control of Joint Velocities

Abstract Nowadays, robots are applied in dynamic environments. For a robust operation, the motion planning module must consider other tasks besides reaching a specified pose: (self) collision avoidance, joint limit avoidance, keeping an advantageous configuration, etc. Each task demands different joint control commands, which may counteract each other. We present a hierarchical control that, depending on the robot and environment state, determines online a suitable priority among those tasks. Thereby, the control command of a lower-prioritized task never hinders the control command of a higher-prioritized task. We ensure smooth control signals also during priority rearrangement. Our hierarchical control computes reference joint velocities. However, the underlying concepts of hierarchical control differ when using joint accelerations or joint torques as control signals instead. So, as a further contribution, we provide a comprehensive discussion on how joint velocity control, joint acceleration control, and joint torque control differ in hierarchical task control. We validate our formulation in an experiment on hardware.

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Institutions

Publication Details

Journal
Journal of Intelligent & Robotic Systems
Published
2024-10-11
DOI
https://doi.org/10.1007/s10846-024-02182-4
Citations
3
Primary Topic
Robotic Mechanisms and Dynamics
Type
article
Field-Weighted Citation Impact
0.98

Funders

Controls
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article

Energy-Aware Hierarchical Control of Joint Velocities

Daniel Hornung, Daniel Rixen, Jonas Wittmann, Korbinian Griesbauer
3 citations
Journal of Intelligent & Robotic Systems
Robotic Mechanisms and Dynamics
0.98
article

Energy-Aware Hierarchical Control of Joint Velocities

Daniel Hornung, Daniel Rixen, Jonas Wittmann, Korbinian Griesbauer
article en
3 citations

Abstract

Abstract Nowadays, robots are applied in dynamic environments. For a robust operation, the motion planning module must consider other tasks besides reaching a specified pose: (self) collision avoidance, joint limit avoidance, keeping an advantageous configuration, etc. Each task demands different joint control commands, which may counteract each other. We present a hierarchical control that, depending on the robot and environment state, determines online a suitable priority among those tasks. Thereby, the control command of a lower-prioritized task never hinders the control command of a higher-prioritized task. We ensure smooth control signals also during priority rearrangement. Our hierarchical control computes reference joint velocities. However, the underlying concepts of hierarchical control differ when using joint accelerations or joint torques as control signals instead. So, as a further contribution, we provide a comprehensive discussion on how joint velocity control, joint acceleration control, and joint torque control differ in hierarchical task control. We validate our formulation in an experiment on hardware.

Journal of Intelligent & Robotic SystemsVol. 110(4)
Technical University of Munich (DE)
Technische Universität München
Sustainable cities and communities
Openalex Percentile: Top 23%
Robotic Mechanisms and Dynamics
0.98
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