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An assistive robot to support dressing – strategies for planning and error handling

机译:支持修整的辅助机器人–规划和错误处理策略

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摘要

Assistive robots are emerging to address a social need due to changing demographic trends such as an ageing population. The main emphasis is to offer independence to those in need and to fill a potential labour gap in response to the increasing demand for caregiving. This paper presents work undertaken as part of a dressing task using a compliant robotic arm on a mannequin. Several strategies are explored on how to undertake this task with minimal complexity and a mix of sensors. A Vicon tracking system is used to determine the arm position of the mannequin for trajectory planning by means of waypoints. Methods of failure detection were explored through torque feedback and sensor tag data. A fixed vocabulary of recognised speech commands was implemented allowing the user to successfully correct detected dressing errors. This work indicates that low cost sensors and simple HRI strategies, without complex learning algorithms, could be used successfully in a robot assisted dressing task.
机译:由于人口趋势(例如人口老龄化)的变化,辅助机器人正在满足社会需求。主要重点是为有需要的人提供独立性并填补潜在的劳动力缺口,以应对日益增长的护理需求。本文介绍了在人体模型上使用顺应性机械臂进行修整任务的工作。探讨了如何以最小的复杂度和混合传感器来执行此任务的几种策略。 Vicon跟踪系统用于通过航路点确定人体模型的手臂位置以进行轨迹规划。通过扭矩反馈和传感器标签数据探索了故障检测方法。实施了已识别语音命令的固定词汇表,允许用户成功地纠正检测到的着装错误。这项工作表明,低成本的传感器和简单的HRI策略,无需复杂的学习算法,就可以成功地用于机器人辅助的修整任务。

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