Hierarchical Task-Oriented Whole-Body Locomotion of a Walking Exoskeleton Using Adaptive Dynamic Motion Primitive for Cart Pushing

This paper proposes a hierarchical task-oriented whole-body locomotion framework for the exoskeleton walking-cart pushing (EWCP) task, which includes a straight gait and a bypassing gait, allowing the exoskeleton robot to avoid obstacles during walking. In this framework, the core components are gait planning and phase estimation for locomotion in unstructured environments. Notably, our mobile redundancy exoskeleton system can provide more flexibility and versatility in manipulation when performing complex tasks. For the hierarchical task-oriented whole-body locomotion, the detour gait consists of straight lines and turning shapes so that the EWCP system can avoid obstacles on the ground. For gait planning, we use the dynamic motion primitives to learn the joint motion trajectory of whole-body locomotion, which has good generalization ability and adaptability with respect to the gait. For phase estimation, the current gait phase can be estimated from the joint angles. Additionally, we design an task switching mechanism, where the exoskeleton system can switch different configurations flexibly for different scenarios, such as track switching only with both feet supported. And the phase estimation and gait switching strategy ensure the stability of task switching. The experimental results show that the exoskeleton can effectively accomplish EWCP tasks in an environment with obstacles. Our work has also shown that even some challenging motion tasks can be implemented with relatively simple controllers, which greatly simplifies the design of control systems.
Note to Practitioners
—This paper is motivated by issues of hierarchical tasks of the lower limb exoskeleton. Traditional exoskeletons cannot achieve obstacle avoidance in complex scenes because they do not have enough degrees of freedom or they do not use hierarchical locomotion. In this paper, a hierarchical task-oriented whole-body locomotion is proposed, which includes a straight gait and a bypassing gait, allowing the exoskeleton robot to avoid obstacles during walking. For gait planning, we use DMP to generate the gait trajectory, which can ensure the smoothness of trajectory. For phase estimation, the current gait phase can be estimated from the joint angles. Additionally, we design an task switching mechanism, where the exoskeleton system can switch different configurations flexibly for different scenarios, such as track switching only with both feet supported. And the phase estimation and gait switching strategy ensure the stability of task switching. The proposed hierarchical task-oriented whole-body locomotion framework is expected to be applied to exoskeletons to assist patients in rehabilitation training and users in mobility in daily life. Additionally, the proposed framework uses a series of motion primitives to learn and reproduce the trajectory and update it online, which requires a heavy computation load calculation to ensure the update speed of the trajectory. Therefore, we expect to reduce computation complexity for a walking exoskeleton in the future.