A task-level approach for the position control of macro-mini robotic systems

This article proposes a new task level approach to control the position of macro-mini robotic systems. The proposed method combines redundancy resolution and PI compensation. Taking advantage of the redundancy resolution, this control method accounts for the differences in the dynamics of the macro robot and the mini robot during positioning tasks while ensuring that both robots respect their mechanical limits. The combination with a PI compensation improves the control performance in tracking tasks. This work also presents the adaptation of two other separate methods, namely mid-ranging control and Model Predictive Control, to macro-mini robots. A new macro-mini robot is introduced and experiments, in which the three control methods perform the same trajectories, are conducted. The control performance as well as the advantages or drawbacks of each method are compared. The general behavior of each robot component is also observed and analyzed. Finally, several practical issues and potential future work are discussed.

Authors

Institutions

Publication Details

Journal
Proceedings of the Institution of Mechanical Engineers Part I Journal of Systems and Control Engineering
Published
2025-03-24
DOI
https://doi.org/10.1177/09596518251324684
Citations
1
Primary Topic
Robot Manipulation and Learning
Type
article
Field-Weighted Citation Impact
1.21
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A task-level approach for the position control of macro-mini robotic systems

Clément Gosselin, Tan-Sy Nguyen
1 citations
Proceedings of the Institution of Mechanical Engineers Part I Journal of Systems and Control Engineering
Robot Manipulation and Learning
1.21
article

A task-level approach for the position control of macro-mini robotic systems

Clément Gosselin, Tan-Sy Nguyen
article en
1 citations

Abstract

This article proposes a new task level approach to control the position of macro-mini robotic systems. The proposed method combines redundancy resolution and PI compensation. Taking advantage of the redundancy resolution, this control method accounts for the differences in the dynamics of the macro robot and the mini robot during positioning tasks while ensuring that both robots respect their mechanical limits. The combination with a PI compensation improves the control performance in tracking tasks. This work also presents the adaptation of two other separate methods, namely mid-ranging control and Model Predictive Control, to macro-mini robots. A new macro-mini robot is introduced and experiments, in which the three control methods perform the same trajectories, are conducted. The control performance as well as the advantages or drawbacks of each method are compared. The general behavior of each robot component is also observed and analyzed. Finally, several practical issues and potential future work are discussed.

Proceedings of the Institution of Mechanical Engineers Part I Journal of Systems and Control EngineeringVol. 239(7)
Université Laval (CA)
Openalex Percentile: Top 24%
Robot Manipulation and Learning
1.21
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.