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.
翻译：人类半静态和拥挤环境中的机器人导航可能导致冷冻问题, 机器人无法移动, 因为有人类站在其路径上, 没有其他路径。 经典的机器人导航方法不能解决问题。 在这种情况下, 机器人可以与人类互动, 而不是将之视为没有防火障碍。 在这项工作中, 我们为一个轮式人类机器人提议一种机器人行为, 它对机器人因存在人类而冻结时清理其路径的社会规范有不满。 行为由两个模块组成:(1) 一个探测模块, 利用经过训练的Yolo v3算法来探测人类手和人类武器。 (2) 一个手势模块, 使用经过训练的模拟政策, 使用“ 优化政策” 优化算法进行模拟。 使用 ROS 框架完成两种模型的操作。
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