Enhancing the capabilities of approaching to service scenarios and settling for intelligent wheelchair robots

Abstract

Wheelchairs are the evaded partner in the lives of many differently-abled people to support their day-to-day activities. Manual and powered wheelchairs fail to meet the docking behavior for a specific task on the table. As the main aim of this research, a human study was performed to identify the docking behavior of a wheelchair to the table or desk in four different scenarios such as writing, reading, eating, and using a Laptop. With 3D point cloud data, this paper introduces an algorithm for automatically detecting secure docking locations at rectangular docking structures (tables, desks) with proper alignment knowledge. Within the sense of delivering advanced driving assistance for powered wheelchair users, the secure docking areas will then be given as priorities to an autonomous route designer. The experimental findings show that the proposed wheelchair docking system is capable of maintaining user comfort during approaches.