Enhancing Elderly Mobility: A Sturdy, Two-Body Robot for Handlebar Placement in Any Location
Enhancing Elderly Mobility: A Sturdy, Two-Body Robot for Handlebar Placement in Any Location
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DOI：
10.1109/lra.2024.3359549
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发表时间：
2024-03
影响因子：
5.2
通讯作者：
Ieee Roberto Bolli Jr Graduate Student Member;Ieee H. Harry Asada Life Fellow
中科院分区：
文献类型：
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作者：
Ieee Roberto Bolli Jr Graduate Student Member;Ieee H. Harry Asada Life Fellow
扶手杆被广泛用于为老年人提供日常活动的支持，但其实用性受到房间几何形状、安装成本和其他运动的潜在阻碍的限制。我们通过一个移动的机器人来解决这些挑战，这个机器人可以在空间的任何一点放置一个机器人，以最佳地支持姿势转换。通过对老年人和护理专业人员的调查，我们提出了一种新的两体机器人结构，由两个小占地面积的移动的基地连接的四连杆机构。运动学分析表明，该结构能够承受人体的全部重量，并提供可靠的支撑，不会滑动或倾倒。该机器人的最小宽度为29.2厘米，可在有限的空间内折叠，使其成为有史以来最薄的移动的姿势辅助机器人。几何路径跟踪的控制计划，提出了推广到所有机器人与两个耦合，非完整，移动的基地。这包括一个领导者-跟随者方案，以及对路径跟踪和航位推算的各种增强，使机器人能够准确地遵循一系列航路点。在0.4 m长的测试路径上，尽管胎面滑动严重，但仅使用胎面上的编码器，1：4比例的机器人模型实现了0.01 m的均方根误差和与路径终点0.015 m的偏差。和机器人框架。最后，机器人的效用，支持日常生活活动的概念证明。
Grab bars are widely used to provide elderly persons with support for daily activities, but their utility is limited by room geometry, cost of installation, and potential obstruction of other movements. We address these challenges through a mobile robot that can place a handlebar at any point in space, to optimally support postural transitions. Informed by a survey of elderly people and care professionals, we propose a novel two-body robot structure, consisting of two small-footprint mobile bases connected by a four bar linkage. Kinematic analysis shows that the structure can bear the entire weight of a human body, and provides secure support without sliding or tipping. The robot has a minimum width of 29.2 cm to be maneuverable within confined spaces, making it likely the slimmest robot ever developed for mobile postural assistance. A control plan for geometric path tracking is proposed that is generalizable to all robots with two coupled, nonholonomic, mobile bases. This consists of a leader-follower scheme as well as various enhancements to path tracking and dead reckoning that allow the robot to accurately follow a series of waypoints. On an 0.4 m long test path, despite significant tread slippage, a 1:4 scale model of the robot achieved a root mean square error of 0.01 m and a deviation of 0.015 m from the path terminus, using only the encoders on the treads and robot frame. Finally, the robot's utility for supporting activities of daily living is demonstrated as a proof of concept.