Adaptive Passivation of Admittance Controllers by Bypassing Power to Null Space on Redundant Manipulators

The significance of physical human-robot interaction (pHRI) with collaborative robots in the industry is growing steadily. Within this domain, an admittance controller is crucial for enabling robots to follow or assist human intentions. However, a persistent challenge with admittance controllers is ensuring their passivity. Various strategies have been developed to address this issue by adjusting the control signals derived from the admittance model. While these strategies achieve passivity, they often inadvertently impact collaborative performance, preventing the system from accurately aligning with the intended dynamics. Accordingly, this paper introduces an adaptive hierarchical control approach for redundant robots to handle this problem. This approach diverts non-passive power into the null space without diminishing the robot’s responsiveness to human input. Implementing this null-space controller involves the dynamic adjustment of compliance control error, ensuring joint limit avoidance while facilitating integration with energy tanks for enhanced reliability. Moreover, the method enables the calculation of adaptive error gain in a closed form, simplifying its real-time application. Experimental validation with a 7-DOF manipulator showed a reduction of non-passive energy from 1.61 J to 0.12 J without compromising task performance.

Authors

Institutions

Publication Details

Published
2024-10-14
DOI
https://doi.org/10.1109/iros58592.2024.10801296
Citations
1
Primary Topic
Modular Robots and Swarm Intelligence
Type
article
Field-Weighted Citation Impact
0.21
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Adaptive Passivation of Admittance Controllers by Bypassing Power to Null Space on Redundant Manipulators

Hyouk Ryeol Choi, Ja Choon Koo, Hyungpil Moon, Eun Jeong Song et al.
1 citations
Modular Robots and Swarm Intelligence
0.21
article

Adaptive Passivation of Admittance Controllers by Bypassing Power to Null Space on Redundant Manipulators

Hyouk Ryeol Choi, Ja Choon Koo, Hyungpil Moon, Eun Jeong Song, Dongryul Oh, Yesom Yun
article en
1 citations

Abstract

The significance of physical human-robot interaction (pHRI) with collaborative robots in the industry is growing steadily. Within this domain, an admittance controller is crucial for enabling robots to follow or assist human intentions. However, a persistent challenge with admittance controllers is ensuring their passivity. Various strategies have been developed to address this issue by adjusting the control signals derived from the admittance model. While these strategies achieve passivity, they often inadvertently impact collaborative performance, preventing the system from accurately aligning with the intended dynamics. Accordingly, this paper introduces an adaptive hierarchical control approach for redundant robots to handle this problem. This approach diverts non-passive power into the null space without diminishing the robot’s responsiveness to human input. Implementing this null-space controller involves the dynamic adjustment of compliance control error, ensuring joint limit avoidance while facilitating integration with energy tanks for enhanced reliability. Moreover, the method enables the calculation of adaptive error gain in a closed form, simplifying its real-time application. Experimental validation with a 7-DOF manipulator showed a reduction of non-passive energy from 1.61 J to 0.12 J without compromising task performance.

Sungkyunkwan University (KR)
Openalex Percentile: Top 48%
Modular Robots and Swarm Intelligence
0.21
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.