论文标题
快速地区的快速，自主，两足步行行为
A Fast, Autonomous, Bipedal Walking Behavior over Rapid Regions
论文作者
论文摘要
在试图在为人类建立的世界中执行有用任务的类人形机器人时，我们解决了自主运动的问题。人形机器人规划和控制算法在崎rough地形上行走的算法变得越来越有能力。同时，市售的深度摄像机已经变得越来越准确，而GPU计算已成为AI研究中的主要工具。在本文中，我们提出了一个新建造的行为控制系统，用于实现快速，自主，两足步行，而无需暂停或审议。我们使用最近发布的快速平面区域感知算法，基于高度图的身体路径计划者，A*脚步计划器和基于动量的步行控制器来实现这一目标。我们将这些元素放在一起以形成一个由现代软件开发实践和仿真工具支持的行为控制系统。
In trying to build humanoid robots that perform useful tasks in a world built for humans, we address the problem of autonomous locomotion. Humanoid robot planning and control algorithms for walking over rough terrain are becoming increasingly capable. At the same time, commercially available depth cameras have been getting more accurate and GPU computing has become a primary tool in AI research. In this paper, we present a newly constructed behavior control system for achieving fast, autonomous, bipedal walking, without pauses or deliberation. We achieve this using a recently published rapid planar regions perception algorithm, a height map based body path planner, an A* footstep planner, and a momentum-based walking controller. We put these elements together to form a behavior control system supported by modern software development practices and simulation tools.
