Learning, Generalization, and Obstacle Avoidance with Dynamic Movement Primitives and Dynamic Potential Fields
In order to offer simple and convenient assistance for the elderly and disabled to take care of themselves, we propose a general learning and generalization approach for a service robot to accomplish specified tasks autonomously in an unstructured home environment. This approach firstly learns the r...
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MDPI AG
2019-04-01
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Series: | Applied Sciences |
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Online Access: | https://www.mdpi.com/2076-3417/9/8/1535 |
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author | Mingshan Chi Yufeng Yao Yaxin Liu Ming Zhong |
author_facet | Mingshan Chi Yufeng Yao Yaxin Liu Ming Zhong |
author_sort | Mingshan Chi |
collection | DOAJ |
description | In order to offer simple and convenient assistance for the elderly and disabled to take care of themselves, we propose a general learning and generalization approach for a service robot to accomplish specified tasks autonomously in an unstructured home environment. This approach firstly learns the required tasks by learning from demonstration (LfD) and represents the learned tasks with dynamic motion primitives (DMPs), so as to easily generalize them to a new environment only with little modification. Furthermore, we integrate dynamic potential field (DPF) with the above DMPs model to realize the autonomous obstacle avoidance function of a service robot. This approach is validated on the wheelchair mounted robotic arm (WMRA) by performing serial experiments of placing a cup on the table with an obstacle or without obstacle on its motion path. |
first_indexed | 2024-12-14T03:52:48Z |
format | Article |
id | doaj.art-4d50c5ab8c6a4510a077bba54a9869d5 |
institution | Directory Open Access Journal |
issn | 2076-3417 |
language | English |
last_indexed | 2024-12-14T03:52:48Z |
publishDate | 2019-04-01 |
publisher | MDPI AG |
record_format | Article |
series | Applied Sciences |
spelling | doaj.art-4d50c5ab8c6a4510a077bba54a9869d52022-12-21T23:18:10ZengMDPI AGApplied Sciences2076-34172019-04-0198153510.3390/app9081535app9081535Learning, Generalization, and Obstacle Avoidance with Dynamic Movement Primitives and Dynamic Potential FieldsMingshan Chi0Yufeng Yao1Yaxin Liu2Ming Zhong3State Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin 150001, ChinaState Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin 150001, ChinaState Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin 150001, ChinaState Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin 150001, ChinaIn order to offer simple and convenient assistance for the elderly and disabled to take care of themselves, we propose a general learning and generalization approach for a service robot to accomplish specified tasks autonomously in an unstructured home environment. This approach firstly learns the required tasks by learning from demonstration (LfD) and represents the learned tasks with dynamic motion primitives (DMPs), so as to easily generalize them to a new environment only with little modification. Furthermore, we integrate dynamic potential field (DPF) with the above DMPs model to realize the autonomous obstacle avoidance function of a service robot. This approach is validated on the wheelchair mounted robotic arm (WMRA) by performing serial experiments of placing a cup on the table with an obstacle or without obstacle on its motion path.https://www.mdpi.com/2076-3417/9/8/1535service robotsdynamic motion primitives (DMPs)dynamic potential field (DPF)obstacle avoidance |
spellingShingle | Mingshan Chi Yufeng Yao Yaxin Liu Ming Zhong Learning, Generalization, and Obstacle Avoidance with Dynamic Movement Primitives and Dynamic Potential Fields Applied Sciences service robots dynamic motion primitives (DMPs) dynamic potential field (DPF) obstacle avoidance |
title | Learning, Generalization, and Obstacle Avoidance with Dynamic Movement Primitives and Dynamic Potential Fields |
title_full | Learning, Generalization, and Obstacle Avoidance with Dynamic Movement Primitives and Dynamic Potential Fields |
title_fullStr | Learning, Generalization, and Obstacle Avoidance with Dynamic Movement Primitives and Dynamic Potential Fields |
title_full_unstemmed | Learning, Generalization, and Obstacle Avoidance with Dynamic Movement Primitives and Dynamic Potential Fields |
title_short | Learning, Generalization, and Obstacle Avoidance with Dynamic Movement Primitives and Dynamic Potential Fields |
title_sort | learning generalization and obstacle avoidance with dynamic movement primitives and dynamic potential fields |
topic | service robots dynamic motion primitives (DMPs) dynamic potential field (DPF) obstacle avoidance |
url | https://www.mdpi.com/2076-3417/9/8/1535 |
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