Real-time walking pattern generation for a lower limb exoskeleton, implemented on the Exoped robot

Lower extremity exoskeletons have been developed as a motion assistive technology in recent years. Walking pattern generation is a fundamental topic in the design of these robots. The usual approach with most exoskeletons is to use a pre-recorded pattern as a look-up table. There are some deficiencies with this method, including data storage limitation and poor regulation relating to the walking parameters. In addition, the walking parameters can be taken in hand very hard. Therefore modeling the human walking pattern is required. The few existing models provide piece by piece walking patterns, only generating at the beginning of each stride. In this paper, a real-time walking pattern generation method is provided which enables changing the parameters during the stride. For this purpose, two feedback controlled third order systems are proposed as real-time trajectory planners for generating the trajectories of the x and y components of each joint's position. The boundary conditions of the trajectories are determined to prevent backward balance loss by appropriate displacement of the center of mass. In addition, a cost function is intended for each trajectory planner in order to increase the smoothness of trajectories. Optimization technique is used to design the feedback controller for tracking the boundary conditions in such a way that the cost function is minimized. Finally, the proper joint angles are generated using inverse kinematics transformation. The performance of the proposed pattern generator is verified via real experiments on the Exoped robot. (C) 2019 Elsevier B.V. All rights reserved.