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

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

外文摘要：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.

外文关键词：

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

作者：

Kaiyuan Chen、Runda Zhang、Miao Wang、Yiran Wang、Huatang Zeng、Wannian Liang

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作者单位：

Vanke School of Public Health,Tsinghua Institute for Healthy China,Tsinghua University,Beijing 100084,China

School of Automation,Beijing Insti-tute of Technology,Beijing 100081,China

Shenzhen Health Development Research and Data Management Center,Shenzhen 515100,China

关键词：

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

出版年：

2024

DOI：

10.15918/j.jbit1004-0579.2023.156

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

年,卷(期)：2024.33(6)