A collaborative telerobotics network framework with hand gesture interface and conflict prevention
A collaborative telerobotics network framework with hand gesture interface and conflict prevention
复制标题
具有手势界面和冲突预防功能的协作远程机器人网络框架
DOI：
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发表时间：
2013
期刊：
影响因子：
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通讯作者：
S. Nof
中科院分区：
文献类型：
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作者：
Hao Zhong;J. Wachs;S. Nof
手势控制具有手势的表现力和自然度，是遥操作机器人控制的一种有效方式。本文讨论了一种协作式控制系统，其中远程机器人由一组分布在网络上的操作员同时控制以完成一项任务。为了方便人机交互，引入了手势识别的计算机视觉算法。这些手势被转换成命令，传递给机器人，以灵活地完成任务。来自多个操作员的命令由协作协议聚合到单个控制流中。聚合根据运营商的表现进行更新。设计了一个分布式冲突和错误检测-预测网络，并将其应用于机器人核退役任务协同控制的案例研究。操作员使用手势命令远程机器人拆除受污染地区的设施。检验了这一假设，即协同控制比标准的单操作员控制更有效，更不容易发生冲突/错误。在协作期间，操作员同时执行手势命令来控制一组机器人。在杂乱的背景下，该系统可以可靠地识别操作员的手，准确率为96%。专家和新手操作员之间的协作可以将完成多步骤任务的时间平均减少45%。
Hand gesture control is an efficient modality for telerobot control because of gesture expressiveness and naturalness. This paper discusses a collaborative cybernetic system, where telerobots are controlled simultaneously by a group of distributed operators over the network to accomplish a task. Computer vision algorithms for hand gesture recognition are introduced to facilitate the human–robot interface. The gestures are converted into commands that are delivered to robots for dexterous task completion. Commands from multiple operators are aggregated by a collaboration protocol into a single control stream. The aggregation is updated according to operators’ performance. A distributed conflict and error detection–prediction network is designed and applied to a case study of collaborative control for a robotic nuclear decommissioning task. Operators use hand gestures to command telerobots to disassemble facilities in a contaminated area. The hypothesis is tested that collaborative control is more effective and less susceptible to conflicts/errors than the standard single-operator control. During collaboration, operators performed gesture commands simultaneously to control a set of robots. The system can reliably recognise operators’ hands with a 96% accuracy in cluttered backgrounds. Collaboration between expert and novice operators can reduce the time to complete a multi-step task by 45% on average.