A Real-Time Near Optimal Trajectory Planning and Control Scheme for Autonomous Wheelchair Evacuation Tasks

Kaiyuan Chen ¹Runda Zhang ²Miao Wang ¹Yiran Wang ¹Huatang Zeng ³Wannian Liang¹

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作者信息

1. Vanke School of Public Health,Tsinghua Institute for Healthy China,Tsinghua University,Beijing 100084,China
2. School of Automation,Beijing Insti-tute of Technology,Beijing 100081,China
3. Vanke School of Public Health,Tsinghua Institute for Healthy China,Tsinghua University,Beijing 100084,China;Shenzhen Health Development Research and Data Management Center,Shenzhen 515100,China
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Abstract

Motion planning and control of autonomous mobile robots(AMRs)have attracted widespread attention in recent years.As the problem of aging intensifies,it is significant to develop AMRs for the wellbeing of old people.In this paper,a novel long short-term memory(LSTM)-recurrent deep neural network(RDNN)based motion planning and control strategy with data aggregation mechanism is developed for autonomous wheelchairs(AWC)to send the seniors to the exit of the nursing home in a timely manner when emergencies happen.The proposed scheme is ver-ified to be feasible,efficient and robust.

Key words

trajectory optimization/autonomous mobile robots(AMRs)/recurrent deep neural net-work(RDNN)/long short-term memory(LSTM)

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出版年

2024

北京理工大学学报(英文版)

北京理工大学

北京理工大学学报(英文版)

影响因子：0.168

ISSN：1004-0579

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