A review of full-stack autonomous obstacle avoidance for assistive robots for the disabled
Abstract
With the intensification of population aging and the increasing awareness of protecting the rights of the disabled, significant progress has been made in assistive robots for visually impaired people, the mobility impairments and other groups. Research in this field focuses on four key technical dimensions: environmental perception, obstacle recognition and classification, path planning and obstacle avoidance algorithms, and scenario-based applications. This analysis particularly focuses on the ability of multi-sensor fusion to acquire spatial information in complex and dynamic environments, and reviews the technological evolution in target detection, semantic understanding, and passable area determination. The work further explores algorithms ranging from global path planning to local obstacle avoidance strategies, as well as reinforcement learning and multi-algorithm integration. Furthermore, this narrative review synthesizes the current research on assistive technologies, including guide robots for the visually impaired, intelligent mobility platforms for wheelchair users, and solutions adaptable to both indoor and outdoor environments. The insights derived from this review offer a reliable foundation to support the travel and daily activities of people with disabilities.
