首页> 外文会议>Intelligent Robots and Systems, 2004. (IROS 2004). Proceedings. 2004 IEEE/RSJ International Conference on >Human robot interference adapting control coordinating human following and task execution
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Human robot interference adapting control coordinating human following and task execution

机译:协调人的跟随与任务执行的人机干涉自适应控制

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It is important for human symbiotic robots working near humans to have the adaptability to reliably follow force from humans while maintaining task performance despite unexpected disturbances. Thus, in the current study we propose a coordination control method of concurrently accomplishing task execution and human following even when physical interference and contact (PIFACT) occur with humans. First, functional requirements for the control method are specified from the viewpoints of motion-phase transition capability, time management characteristic of respective motion phase, and forms of task-performable human-following motion. Next, a control system architecture satisfying the requirements is presented. In addition, we describe a method of quantitatively representing a rule of task to process PIFACT adapting motions that allow achieving both human following and task performance according to the attributes of imposed tasks. Finally, experiments were carried out in which PlFACT was induced between humans and a full-size anthropomorphic robot equipped with the control architecture. We evaluated the results in terms of the comparison of variations of hand orientation and position while following humans during PIFACT among conditions where tasks with diverse rules were imposed on the robot. Evaluation of experiments demonstrates the proposed control architecture is useful for coordinating task execution and human following necessary for elevating human symbiotic robots.
机译:对于在人类附近工作的人类共生机器人来说,重要的是要具有适应能力,使其能够可靠地跟随人类的力量,同时即使遇到意外干扰也能保持任务性能。因此,在当前的研究中,我们提出了一种协调控制方法,即使在与人发生物理干扰和接触(PIFACT)的情况下,也能同时完成任务执行和人的跟随。首先,从运动阶段过渡能力,各个运动阶段的时间管理特性以及可执行任务的人类跟随运动的形式的角度来指定控制方法的功能要求。接下来,提出一种满足要求的控制系统架构。此外,我们描述了一种定量表示任务规则的方法,以处理PIFACT适应运动,该运动允许根据所施加任务的属性实现人工跟踪和任务执行。最后,进行了在人和配备了控制架构的全尺寸拟人化机器人之间诱导PlFACT的实验。我们比较了在PIFACT期间跟随人类的手方向和位置变化的比较情况下的结果,在PIFACT期间,对机器人施加了不同规则的任务。实验评估表明,提出的控制架构可用于协调任务执行和提升人类共生机器人所必需的人类遵循。

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