Research on Control Methods of Electric Assistive Walkers Based on 3D Vision

This study proposes a control method for electric assistive walkers using 3D vision and VFF (virtual force fields). The method computes the users CoG (center of gravity) and toe direction in real time to guide the walker for target tracking and obstacle avoidance. Combined with a grid-based approach, the VFF model dynamically adjusts forces to ensure the walker follows the user while avoiding obstacles. Simulation experiments in UE5 (Unreal Engine 5) demonstrate stable and responsive motion control, highlighting the potential of 3D vision-based methods to enhance the safety and usability of electric assistive walkers.