Optimization-Based Adaptive Assistance for Lower Limb Exoskeleton Robots With a Robotic Walker via Spatially Quantized Gait

Gait training with human-like gait patterns can be provided by lower limb exoskeletons (LLEs) for patients with gait impairments. For patients with little effort to keep balance, using a mobile robotic walker to assist gait training with LLEs is an effective way. Since gait patterns are varying with walking speeds, it is a critical issue to coordinated control the robotic walker and the exoskeleton to obtain a natural and human-like walking posture. In this paper, a novel adaptive assistance approach named SQG-OPT is proposed to tackle the problem, which comprises of two parts: the Spatially Quantized Gait (SQG) and the optimization. The SQG generates reference joint angles and reference trajectory of the Center Of Mass (COM) for the human-exoskeleton system in space domain. The optimization part is constructed to convert the reference joint angles from the space domain to the time domain, which is based on the dynamics model of the human-exoskeleton-walker system and adaptive to different walking speeds. The proposed approach has been tested on the robot simulation platform CoppeliaSim, the experimental results indicate that the proposed approach can generate human-like gait patterns for different walking speeds from 0 to 0.8 m/s. Additionally, in comparison with other methods, the proposed approach has a better performance on the movement tracking of the COM for a natural walking posture.
Note to Practitioners
—The coordinated control is important for the exoskeleton robot with a mobile robotic walker, one of the potential challenge is the adaptive coordinated motion planning for these robotic devices. The proposed approach is for the coordinated control of the exoskeleton robots with a robotic walker and adaptive to different walking speeds, which may inspires more extended coordinated control strategies for human-exoskeleton systems in more gait training applications. The proposed approach is also potential for the coordinated motion planning of the other human-centered assistance robots, such as the wheeled walking assistance robots for the elderly.