While powered wheelchairs reduce physical fatigue as opposed to manual wheelchairs for individuals with mobility impairment, they demand high cognitive workload due to information processing, decision making and motor coordination. Current autonomous systems lack social awareness in navigation and transparency in decision-making, leading to decreased perceived safety and trust from the user and others in context. This work proposes Socially Aware Autonomous Transparent Transportation (SAATT) Navigation framework for wheelchairs as a potential solution. By implementing a Large Language Model (LLM) informed of user intent and capable of predicting other peoples' intent as a decision-maker for its local controller, it is able to detect and navigate social situations, such as passing pedestrians or a pair conversing. Furthermore, the LLM textually communicates its reasoning at each waypoint for transparency. In this experiment, it is compared against a standard global planner, a representative competing social navigation model, and an Ablation study in three simulated environments varied by social levels in eight metrics categorized under Safety, Social Compliance, Efficiency, and Comfort. Overall, SAATT Nav outperforms in most social situations and equivalently or only slightly worse in the remaining metrics, demonstrating the potential of a socially aware and transparent autonomous navigation system to assist wheelchair users.
CoNav Chair: Design of a ROS-based Smart Wheelchair for Shared Control Navigation in the Built Environment
University of Michigan（密歇根大学）；College of Literature, Science, and the Arts, University of Michigan（密歇根大学文学、科学与艺术学院）；University of Michigan Health（密歇根大学医疗系统）
Autonomous Mobile Robot Navigation in Uneven and Unstructured Indoor Environments
The Chinese University of Hong Kong（香港中文大学）；The University of British Columbia（不列颠哥伦比亚大学）；National Institute of Advanced Industrial Science and Technology（产业技术综合研究所）
CoNav Chair: Development and Evaluation of a Shared Control based Wheelchair for the Built Environment
Department of Civil Engineering, University of Michigan（密歇根大学土木工程系）；College of Literature, Science, and the Arts, University of Michigan（密歇根大学文理学院）；Wheelchair Seating Service, University of Michigan Health（密歇根大学健康学院轮椅适配服务）；Department of Rehabilitation Science and Technology, University of Pittsburgh（匹兹堡大学康复科学与技术系）
S2P2: Self-Supervised Goal-Directed Path Planning Using RGB-D Data for Robotic Wheelchairs
The Hong Kong University of Science and Technology（香港科技大学）；The Hong Kong Polytechnic University（香港理工大学）；the University of California San Diego（加州大学圣迭戈分校）
WheelArm-Sim: A Manipulation and Navigation Combined Multimodal Synthetic Data Generation Simulator for Unified Control in Assistive Robotics
Aerospace and Mechanical Engineering Department, Saint Louis University（圣路易斯大学航空航天与机械工程系）；Computer Science Department, Saint Louis University（圣路易斯大学计算机科学系）
Shared Control of Holonomic Wheelchairs through Reinforcement Learning
Swiss Paraplegic Research, SPF（瑞士瘫痪研究机构）；SCAI Lab, D-HEST, Swiss Federal School of Technology in Zurich - ETH Zurich（SCAI实验室，瑞士联邦理工学院-苏黎世-ETH Zurich）；Centre for Artificial Ingelligece, Zurich University of Applied Sciences - ZHAW. Switzerland（人工智能中心，瑞士应用科学大学-ZHAW）
