The Visual Footsteps Planning System for Exoskeleton Robots Under Complex Terrain

Abstract

The lower limb power-assist exoskeletons are expected to help paraplegic people to walk again in daily life. However, most of these exoskeletons deal with walking in the scene that has been seen or has an external vision sensor, rather than in the unknown environment. It is a great challenge to understand the wear’s intention and plan the footstep sequence in an unknown scene. Moreover, the traditional visual footstep planning is dominated by the robot, which can lead to an awkward trajectory plan. Therefore, we construct a visual footstep planning system and propose an onboard vision planning algorithm based on the Bezier curve to address the previous two problems. Specially, our human–computer interaction system understands the environment and the wearer’s behavior intention by integrating Hololens and Realsense. Then, we apply the Bezier curve to plan footsteps for the first time in the field of the exoskeleton and define two parameters of the Bezier curve, which are more suitable for our exoskeleton system and could increase the planning speed. Finally, we add the tracking feature cost in the cost function, which could better fit the planned footprints to the planned path and make the gait smoother. Extended experimental results show that the average planning time is 67.46% less than that of the traditional search algorithm. Moreover, the effectiveness of our system is also verified on the visual interaction platform.