ZMP Based Gait Generation of AIT Leg Exoskeleton-A Further Gaits Generation

Abstract

This paper is the extension of gait pattern generation of the Asian Institute of Technology’s Leg EXoskeleton (ALEX) and its wearer can walk safety with the passing criteria of Zero Moment Point (ZMP) theorem for static and dynamic considerations respectively. ALEX has 12 DOF (6 DOF for each leg: 3 at the Hip, 1 at the knee and 2 at the ankle), controlled by 12 DC motors. The CAD drawing and assembly of ALEX are exported directly to MATLAB’s Simulink-SimMechanics to obtain accurate position of center of gravity (CG) and moment of inertia of each link. The gait pattern is visually observed using 3D VRML interpreter while ZMP trajectory is monitored using MATLAB’s 2D graphics representation. The further gaits generations in this paper include walking from non-zero initial condition, climbing up the stairs and turning left motions. From previous work, the gait data from simulation has confirmed it effectiveness with the actual hardware. With this further gait generation data, ALEX can be tested to confirm its balance gait motions prior to the real implementation to avoid any undesired motions that could damages to the robot system.

Push recovery control for the underactuated lower extremity exoskeleton based on improved capture point concept

“…Zhang et al (2020) presented a control strategy for a load-carrying exoskeleton, which maintained the consistency of a body ZMP and exoskeleton ZMP. Aphiratsakun et al (2012) used the ZMP theory to control the gait of the ALEX exoskeleton. However, none of these approaches consider the large external interference of the exoskeleton.…”