Adaptive robot climbing with magnetic feet in unknown slippery structure
Firm foot contact is the top priority of climbing robots to avoid catastrophic events, especially when working at height. This study proposes a robust planning and control framework for climbing robots that provides robustness to slippage in unknown environments. The framework includes 1) a center o...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2022-08-01
|
| Series: | Frontiers in Robotics and AI |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/frobt.2022.949460/full |
| _version_ | 1811183201417166848 |
|---|---|
| author | Jee-eun Lee Tirthankar Bandyopadhyay Luis Sentis |
| author_facet | Jee-eun Lee Tirthankar Bandyopadhyay Luis Sentis |
| author_sort | Jee-eun Lee |
| collection | DOAJ |
| description | Firm foot contact is the top priority of climbing robots to avoid catastrophic events, especially when working at height. This study proposes a robust planning and control framework for climbing robots that provides robustness to slippage in unknown environments. The framework includes 1) a center of mass (CoM) trajectory optimization under the estimated contact condition, 2) Kalman filter–like approach for uncertain environment parameter estimation and subsequent CoM trajectory re-planing, and 3) an online weight adaptation approach for whole-body control (WBC) framework that can adjust the ground reaction force (GRF) distribution in real time. Though the friction and adhesion characteristics are often assumed to be known, the presence of several factors that lead to a reduction in adhesion may cause critical problems for climbing robots. To address this issue safely and effectively, this study suggests estimating unknown contact parameters in real time and using the evaluated contact information to optimize climbing motion. Since slippage is a crucial behavior and requires instant recovery, the computation time for motion re-planning is also critical. The proposed CoM trajectory optimization algorithm achieved state-of-art fast computation via trajectory parameterization with several reasonable assumptions and linear algebra tricks. Last, an online weight adaptation approach is presented in the study to stabilize slippery motions within the WBC framework. This can help a robot to manage the slippage at the very last control step by redistributing the desired GRF. In order to verify the effectiveness of our method, we have tested our algorithm and provided benchmarks in simulation using a magnetic-legged climbing robot Manegto. |
| first_indexed | 2024-04-11T09:43:50Z |
| format | Article |
| id | doaj.art-1b9cf1cb18a84b30adcd9593bdc8059e |
| institution | Directory Open Access Journal |
| issn | 2296-9144 |
| language | English |
| last_indexed | 2024-04-11T09:43:50Z |
| publishDate | 2022-08-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Robotics and AI |
| spelling | doaj.art-1b9cf1cb18a84b30adcd9593bdc8059e2022-12-22T04:31:07ZengFrontiers Media S.A.Frontiers in Robotics and AI2296-91442022-08-01910.3389/frobt.2022.949460949460Adaptive robot climbing with magnetic feet in unknown slippery structureJee-eun Lee0Tirthankar Bandyopadhyay1Luis Sentis2Human Centered Robotics Lab, Department of Aerospace Engineering and Engineering Mechanics, The University of Texas at Austin, Austin, TX, United StatesThe Robotics and Autonomous Systems Group, DATA61, CSIRO, Brisbane, QLD, AustraliaHuman Centered Robotics Lab, Department of Aerospace Engineering and Engineering Mechanics, The University of Texas at Austin, Austin, TX, United StatesFirm foot contact is the top priority of climbing robots to avoid catastrophic events, especially when working at height. This study proposes a robust planning and control framework for climbing robots that provides robustness to slippage in unknown environments. The framework includes 1) a center of mass (CoM) trajectory optimization under the estimated contact condition, 2) Kalman filter–like approach for uncertain environment parameter estimation and subsequent CoM trajectory re-planing, and 3) an online weight adaptation approach for whole-body control (WBC) framework that can adjust the ground reaction force (GRF) distribution in real time. Though the friction and adhesion characteristics are often assumed to be known, the presence of several factors that lead to a reduction in adhesion may cause critical problems for climbing robots. To address this issue safely and effectively, this study suggests estimating unknown contact parameters in real time and using the evaluated contact information to optimize climbing motion. Since slippage is a crucial behavior and requires instant recovery, the computation time for motion re-planning is also critical. The proposed CoM trajectory optimization algorithm achieved state-of-art fast computation via trajectory parameterization with several reasonable assumptions and linear algebra tricks. Last, an online weight adaptation approach is presented in the study to stabilize slippery motions within the WBC framework. This can help a robot to manage the slippage at the very last control step by redistributing the desired GRF. In order to verify the effectiveness of our method, we have tested our algorithm and provided benchmarks in simulation using a magnetic-legged climbing robot Manegto.https://www.frontiersin.org/articles/10.3389/frobt.2022.949460/fulltrajectory optimizationclimbing robotswhole-body controllegged robotsoptimizationparameterization |
| spellingShingle | Jee-eun Lee Tirthankar Bandyopadhyay Luis Sentis Adaptive robot climbing with magnetic feet in unknown slippery structure Frontiers in Robotics and AI trajectory optimization climbing robots whole-body control legged robots optimization parameterization |
| title | Adaptive robot climbing with magnetic feet in unknown slippery structure |
| title_full | Adaptive robot climbing with magnetic feet in unknown slippery structure |
| title_fullStr | Adaptive robot climbing with magnetic feet in unknown slippery structure |
| title_full_unstemmed | Adaptive robot climbing with magnetic feet in unknown slippery structure |
| title_short | Adaptive robot climbing with magnetic feet in unknown slippery structure |
| title_sort | adaptive robot climbing with magnetic feet in unknown slippery structure |
| topic | trajectory optimization climbing robots whole-body control legged robots optimization parameterization |
| url | https://www.frontiersin.org/articles/10.3389/frobt.2022.949460/full |
| work_keys_str_mv | AT jeeeunlee adaptiverobotclimbingwithmagneticfeetinunknownslipperystructure AT tirthankarbandyopadhyay adaptiverobotclimbingwithmagneticfeetinunknownslipperystructure AT luissentis adaptiverobotclimbingwithmagneticfeetinunknownslipperystructure |