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

作　　者：Kaiyuan Chen Runda Zhang Miao Wang Yiran Wang Huatang Zeng Wannian Liang 

机构地区：[1]Vanke School of Public Health,Tsinghua Institute for Healthy China,Tsinghua University,Beijing 100084,China [2]School of Automation,Beijing Institute of Technology,Beijing 100081,China [3]Shenzhen Health Development Research and Data Management Center,Shenzhen 515100,China

出　　处：《Journal of Beijing Institute of Technology》2024年第6期481-492,共12页北京理工大学学报（英文版）

基　　金：supported by the Sanming Project of Medicine in Shenzhen(No.SZSM202111001)。

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 verified to be feasible,efficient and robust.

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

分 类 号：TP242[自动化与计算机技术—检测技术与自动化装置] TP18[自动化与计算机技术—控制科学与工程]