A demonstration trajectory segmentation approach for wheelchair‐mounted assistive robots
Abstract Segmentation of demonstration trajectories and learning the contained motion primitives can effectively enhance the assistive robot's intelligence to flexibly reproduce learnt tasks in an unstructured environment. With the aim to conveniently and accurately segment demonstration trajec...
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| Format: | Article |
| Language: | English |
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Wiley
2025-06-01
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| Series: | CAAI Transactions on Intelligence Technology |
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| Online Access: | https://doi.org/10.1049/cit2.12358 |
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| author | Mingshan Chi Yaxin Liu Qiang Zhang Chao Zeng |
| author_facet | Mingshan Chi Yaxin Liu Qiang Zhang Chao Zeng |
| author_sort | Mingshan Chi |
| collection | DOAJ |
| description | Abstract Segmentation of demonstration trajectories and learning the contained motion primitives can effectively enhance the assistive robot's intelligence to flexibly reproduce learnt tasks in an unstructured environment. With the aim to conveniently and accurately segment demonstration trajectories, a novel demonstration trajectory segmentation approach is proposed based on the beta process autoregressive hidden Markov model (BP‐AR‐HMM) algorithm and generalised time warping (GTW) algorithm aiming to enhance the segmentation accuracy utilising acquired demonstration data. This approach first adopts the GTW algorithm to align the multiple demonstration trajectories for the same task. Then, it adopts the BP‐AR‐HMM algorithm to segment the demonstration trajectories, acquire the contained motion primitives, and establish the related task library. This segmentation approach is validated on the 6‐degree‐of‐freedom JACO robotic arm by assisting users to accomplish a holding water glass task and an eating task. The experimental results show that the motion primitives within the trajectories can be correctly segmented with a high segmentation accuracy. |
| format | Article |
| id | doaj-art-a55142d3d84848918bf122cb5b22672d |
| institution | OA Journals |
| issn | 2468-2322 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | Wiley |
| record_format | Article |
| series | CAAI Transactions on Intelligence Technology |
| spelling | doaj-art-a55142d3d84848918bf122cb5b22672d2025-08-20T02:35:01ZengWileyCAAI Transactions on Intelligence Technology2468-23222025-06-0110373875410.1049/cit2.12358A demonstration trajectory segmentation approach for wheelchair‐mounted assistive robotsMingshan Chi0Yaxin Liu1Qiang Zhang2Chao Zeng3School of Navigation and Shipping Shandong Jiaotong University Weihai ChinaState Key Laboratory of Robotics and Systems Harbin Institute of Technology Harbin ChinaSchool of Navigation and Shipping Shandong Jiaotong University Weihai ChinaTAMS (Technical Aspects of Multimodal Systems) Group University of Hamburg Hamburg GermanyAbstract Segmentation of demonstration trajectories and learning the contained motion primitives can effectively enhance the assistive robot's intelligence to flexibly reproduce learnt tasks in an unstructured environment. With the aim to conveniently and accurately segment demonstration trajectories, a novel demonstration trajectory segmentation approach is proposed based on the beta process autoregressive hidden Markov model (BP‐AR‐HMM) algorithm and generalised time warping (GTW) algorithm aiming to enhance the segmentation accuracy utilising acquired demonstration data. This approach first adopts the GTW algorithm to align the multiple demonstration trajectories for the same task. Then, it adopts the BP‐AR‐HMM algorithm to segment the demonstration trajectories, acquire the contained motion primitives, and establish the related task library. This segmentation approach is validated on the 6‐degree‐of‐freedom JACO robotic arm by assisting users to accomplish a holding water glass task and an eating task. The experimental results show that the motion primitives within the trajectories can be correctly segmented with a high segmentation accuracy.https://doi.org/10.1049/cit2.12358assistive robotsmotion primitivespersonal caretrajectory segmentationwheelchair‐mounted robotic arm |
| spellingShingle | Mingshan Chi Yaxin Liu Qiang Zhang Chao Zeng A demonstration trajectory segmentation approach for wheelchair‐mounted assistive robots CAAI Transactions on Intelligence Technology assistive robots motion primitives personal care trajectory segmentation wheelchair‐mounted robotic arm |
| title | A demonstration trajectory segmentation approach for wheelchair‐mounted assistive robots |
| title_full | A demonstration trajectory segmentation approach for wheelchair‐mounted assistive robots |
| title_fullStr | A demonstration trajectory segmentation approach for wheelchair‐mounted assistive robots |
| title_full_unstemmed | A demonstration trajectory segmentation approach for wheelchair‐mounted assistive robots |
| title_short | A demonstration trajectory segmentation approach for wheelchair‐mounted assistive robots |
| title_sort | demonstration trajectory segmentation approach for wheelchair mounted assistive robots |
| topic | assistive robots motion primitives personal care trajectory segmentation wheelchair‐mounted robotic arm |
| url | https://doi.org/10.1049/cit2.12358 |
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