论文标题
在半静态和拥挤的环境中取消机器人的目标行为
Target Reaching Behaviour for Unfreezing the Robot in a Semi-Static and Crowded Environment
论文作者
论文摘要
在人类半静态和拥挤的环境中的机器人导航可能会导致冻结问题，因为人类站在其路径上，机器人无法移动，并且没有其他路径。机器人导航的经典方法不能为此问题提供解决方案。在这种情况下，机器人可以与人类互动以清除其道路，而不是将它们视为一致障碍。在这项工作中，我们为车轮人形机器人提出了一种机器人行为，该机器人机器人的社会规范在机器人被冻结的情况下冻结了人类，以清理其路径。该行为由两个模块组成：1）检测模块，该模块利用了Yolo V3算法训练以检测人的手和人手臂。 2）一个手势模块，该模块利用使用近端策略优化算法在模拟中训练的策略。两种型号的管弦使用是使用ROS框架完成的。
Robot navigation in human semi-static and crowded environments can lead to the freezing problem, where the robot can not move due to the presence of humans standing on its path and no other path is available. Classical approaches of robot navigation do not provide a solution for this problem. In such situations, the robot could interact with the humans in order to clear its path instead of considering them as unanimated obstacles. In this work, we propose a robot behavior for a wheeled humanoid robot that complains with social norms for clearing its path when the robot is frozen due to the presence of humans. The behavior consists of two modules: 1) A detection module, which make use of the Yolo v3 algorithm trained to detect human hands and human arms. 2) A gesture module, which make use of a policy trained in simulation using the Proximal Policy Optimization algorithm. Orchestration of the two models is done using the ROS framework.
