狗驱动机器人:量化狗的问题解决能力

C. Byrne, Jacob Logas, Larry Freil, Courtney Allen, Melissa Baltrusaitis, Vi Nguyen, Christopher Saad, M. Jackson
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引用次数: 5

摘要

训练一只工作犬来完成炸弹探测或搜救等任务可能需要数年时间,成本也很高。由于检测工作需要基于视觉和气味的解决问题的能力,我们已经开始研究如何量化这些能力来评估狗的潜力。为了实现这一目标,我们研究了狗是否以及如何远程驾驶机器人通过一个简单的迷宫。在我们的可行性研究中,狗与安装在一个凸起平台上的功能互动,该功能触发机器人的运动,同时也提供机器人的视觉反馈。这项研究评估了两名参与者驾驶机器人通过直线路线的三种能力(拉扯、按下按钮和接近)。通过确定最佳的机器人-犬交互方法,我们展示了犬将视觉问题解决能力扩展到外部设备的潜力。
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Dog Driven Robot: Towards Quantifying Problem-Solving Abilities in Dogs
Training a working dog for a role such as bomb detection or search and rescue can take years, incurring a large cost. As detection work requires visual and odor-based problem-solving abilities, we have started to investigate how to quantify these abilities to assess a dog's potential. Towards this goal, we studied if and how a dog can remotely drive a robot through a simple maze. In our feasibility study, the dogs interact with an affordance mounted on a raised platform which triggers robot movement while also providing visual feedback from the robot. This study evaluated three affordances (tug, button press, and proximity) on two participants to drive the robot through a straight course. By identifying the best robot-canine interaction method, we show the potential for canines extending visual problem-solving abilities to an external device.
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