Trajectory Generation with Endpoint Regulation and Momentum-Aware Dynamics for Visually Impaired Scenarios
1 School of Information；Software Engineering, University of Electronic Science；Technology of China, Chengdu 610054, Sichuan, P.R. China. 2 School of Medicine, University of Electronic Science；Technology of China, Chengdu, Sichuan, China. 3 Sichuan Provincial Key Laboratory for Human Disease Gene Study, Sichuan Academy of Medical Sciences \& \ Provincial People's Hospital, University of Electronic Science
Yuting Zeng, Manping Fan, You Zhou, Yongbin Yu, Zhiwen Zheng, Jingtao Zhang, Liyong Ren, Zhenglin Yang
Trajectory generation for visually impaired scenarios requires smooth and temporally consistent state in structured, low-speed dynamic environments. However, traditional jerk-based heuristic trajectory sampling with independent segment generation and conventional smoothness penalties often lead to unstable terminal behavior and state discontinuities under frequent regenerating. This paper proposes a trajectory generation approach that integrates endpoint regulation to stabilize terminal states within each segment and momentum-aware dynamics to regularize the evolution of velocity and acceleration for segment consistency. Endpoint regulation is incorporated into trajectory sampling to stabilize terminal behavior, while a momentum-aware dynamics enforces consistent velocity and acceleration evolution across consecutive trajectory segments. Experimental results demonstrate reduced acceleration peaks and lower jerk levels with decreased dispersion, smoother velocity and acceleration profiles, more stable endpoint distributions, and fewer infeasible trajectory candidates compared with a baseline planner.
BUDD-e: an autonomous robotic guide for visually impaired users
Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano（电子、信息与生物工程系，米兰理工学院）；Department of Design, Politecnico di Milano（设计系，米兰理工学院）；Department of Management, Economics and Industrial Engineering, Politecnico di Milano（管理、经济与工业工程系，米兰理工学院）
Panoptic Lintention Network: Towards Efficient Navigational Perception for the Visually Impaired
Institute for Anthropomatics and Robotics, Karlsruhe Institute of Technology（卡尔斯鲁厄理工学院人机与机器人研究所）；Sino-German School, Tongji University（同济大学中德学院）；Hangzhou SurImage Technology Company Ltd.（杭州 SurImage 科技有限公司）；Hangzhou KrVision Technology Company Ltd.（杭州 KrVision 科技有限公司）
Momentum-constrained Hybrid Heuristic Trajectory Optimization Framework with Residual-enhanced DRL for Visually Impaired Scenarios
School of Information；Software Engineering, University of Electronic Science；Sichuan Provincial Key Laboratory for Human Disease Gene Study, Sichuan Academy of Medical Sciences \& Sichuan Provincial People's Hospital, University of Electronic Science；Research Unit for Blindness Prevention, Chinese Academy of Medical Sciences, Sichuan Academy of Medical Sciences；Sichuan Provincial People’s Hospital, Chengdu, Sichuan, China.
Perception Framework through Real-Time Semantic Segmentation and Scene Recognition on a Wearable System for the Visually Impaired
Institute for Anthropomatics and Robotics, Karlsruhe Institute of Technology（卡尔斯鲁厄理工学院人形机器人与智能系统研究所）；Hangzhou SurImage Technology Company Ltd.（杭州 SurImage 科技有限公司）；Hangzhou KrVision Technology Company Ltd.（杭州 KrVision 科技有限公司）
"I am the follower, also the boss": Exploring Different Levels of Autonomy and Machine Forms of Guiding Robots for the Visually Impaired
Institute for AI Industry Research, Tsinghua University（清华大学人工智能产业研究院）；The Hong Kong University of Science and Technology (Guangzhou)（香港科技大学（广州））；The Hong Kong University of Science and Technology（香港科技大学）
