论文标题
通过隐式协调的协作人机探索
Collaborative Human-Robot Exploration via Implicit Coordination
论文作者
论文摘要
本文开发了一种协作人类机器人探索的方法，该方法利用了隐式协调。大多数自主的单机器人探索系统都要求远程操作员向机器人团队提供明确的指导。很少有人考虑如何将人类合作伙伴与机器人一起嵌入到该领域的指导。对人类机器人探索的剩下的挑战是从人类到机器人的目标有效沟通。在本文中，我们开发了一种方法论，该方法从人的头上的头盔深度相机到机器人的头盔深度摄像头以及基于信息增益的探索目标，该方法在人类提供的观点中偏向运动计划。结果是一个航空系统，该航空系统可以安全地访问人类可能无法立即看到或无法达到的利益区域。该方法在模拟和运动捕获领域的硬件实验中进行了评估。模拟和硬件实验的视频可在以下网址提供：https：//youtu.be/7jgkbpvfioe。
This paper develops a methodology for collaborative human-robot exploration that leverages implicit coordination. Most autonomous single- and multi-robot exploration systems require a remote operator to provide explicit guidance to the robotic team. Few works consider how to embed the human partner alongside robots to provide guidance in the field. A remaining challenge for collaborative human-robot exploration is efficient communication of goals from the human to the robot. In this paper we develop a methodology that implicitly communicates a region of interest from a helmet-mounted depth camera on the human's head to the robot and an information gain-based exploration objective that biases motion planning within the viewpoint provided by the human. The result is an aerial system that safely accesses regions of interest that may not be immediately viewable or reachable by the human. The approach is evaluated in simulation and with hardware experiments in a motion capture arena. Videos of the simulation and hardware experiments are available at: https://youtu.be/7jgkBpVFIoE.
