论文标题
使用可预测的人类运动的可及的下限假体中的跳闸恢复
Trip Recovery in Lower-Limb Prostheses using Reachable Sets of Predicted Human Motion
论文作者
论文摘要
较低的损失的人，其中大多数使用被动假体，每年表现出较高的跌倒。动力的下限下肢假肢有可能通过积极帮助用户从绊倒中恢复过来来降低跌倒率，但是人类响应的不可预测性使设计控制者很难确保成功恢复。本文介绍了一种称为Trip-RTD的方法（通过基于可及性的轨迹设计进行trip-rtd恢复在假体中恢复），用于在线轨迹规划，以在跌倒期间和之后的膝盖假体中进行在线轨迹规划，以适应一组对人类行为的可能预测。使用这一预测的人类行为，该提出的方法计算了人类传播系统的一组参数化的轨迹集。为了确保在运行时的安全性，Trip-RTD选择了假体的轨迹，该轨迹确保了达阵的所有可能状态。在模拟的绊倒实验中，基于阶段的控制器无法帮助系统恢复，Trip-RTD在101毫秒以下产生了轨迹，从而导致了所有可行解决方案的成功恢复。
People with lower-limb loss, the majority of which use passive prostheses, exhibit a high incidence of falls each year. Powered lower-limb prostheses have the potential to reduce fall rates by actively helping the user recover from a stumble, but the unpredictability of the human response makes it difficult to design controllers that ensure a successful recovery. This paper presents a method called TRIP-RTD (Trip Recovery in Prostheses via Reachability-based Trajectory Design) for online trajectory planning in a knee prosthesis during and after a stumble that can accommodate a set of possible predictions of human behavior. Using this predicted set of human behavior, the proposed method computes a parameterized reachable set of trajectories for the human-prosthesis system. To ensure safety at run-time, TRIP-RTD selects a trajectory for the prosthesis that guarantees that all possible states of the human-prosthesis system at touchdown arrive in the basin of attraction of the nominal behavior of the system. In simulated stumble experiments where a nominal phase-based controller was unable to help the system recover, TRIP-RTD produced trajectories in under 101 ms that led to successful recoveries for all feasible solutions found.
