Zhao Xiaoming, Chen Wei-Hai, Li Bing, Wu Xingming, Wang Jianhua
School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China.
College of Electrical Engineering and Automation, Shandong University of Science and Technology, Qingdao 266590, China.
Rev Sci Instrum. 2019 Dec 1;90(12):125112. doi: 10.1063/1.5109741.
The mobility on stairways is a daily challenge for seniors and people with dyskinesia. Lower limb exoskeletons can be effective assistants to improve their life quality. In this paper, we present an adaptive stair-ascending gait generation algorithm based on a depth camera for lower limb exoskeletons. We first construct a linked-list-based stairway model with the point cloud captured from the depth camera. Then, an optimal foothold point is calculated based on the linked-list stair model for gait generation. Finally, the exoskeleton takes the stair-ascending gait of healthy people as a reference and generates appropriate gait for the stair. The proposed gait generation algorithm is initially validated through holistic simulation analyses. We tested the stairway modeling algorithm on varieties of indoor and outdoor stairways and evaluated the gait generation algorithm on stairs of different height. The subjects' stair walking tests with lower limb exoskeletons show the effectiveness of the proposed stairway modeling and gait generation approaches.
对于老年人和患有运动障碍的人来说，在楼梯上行走是一项日常挑战。下肢外骨骼可以成为提高他们生活质量的有效辅助工具。在本文中，我们提出了一种基于深度相机的下肢外骨骼自适应上楼梯步态生成算法。我们首先利用从深度相机捕获的点云构建基于链表的楼梯模型。然后，基于链表楼梯模型计算用于步态生成的最佳立足点。最后，外骨骼以上楼梯的健康人的步态为参考，生成适合楼梯的步态。所提出的步态生成算法最初通过整体仿真分析进行了验证。我们在各种室内和室外楼梯上测试了楼梯建模算法，并在不同高度的楼梯上评估了步态生成算法。受试者使用下肢外骨骼进行的楼梯行走测试表明了所提出的楼梯建模和步态生成方法的有效性。
