复杂离散地形上四足机器人的高速控制与导航
High-speed control and navigation for quadrupedal robots on complex and discrete terrain
AI总结：
本文提出一种由规划器与跟踪器组成的分层导航流水线，结合采样优化、神经网络滤波和竞争式生成训练，使四足机器人 Raibo 能在复杂离散地形上实现高速敏捷运动。
摘要：
在离散且几何复杂的环境中实现高速足式导航是一项具有挑战性的任务，因为优化问题具有高自由度动力学特性和长时域、非凸性质。在本工作中，我们提出了一种用于足式机器人的分层导航流水线，使其能够高速穿越此类环境。所提出的流水线由规划器模块和跟踪器模块组成。规划器模块通过基于采样的优化，并利用启发式方法和神经网络进行快速顺序滤波，来寻找物理可行的落足点规划。随后，在物理仿真中执行 rollout，以根据设计的代价函数识别最佳落足点规划，并确认其物理一致性。该分层规划模块同时具备计算高效性和物理准确性。跟踪器的目标是精确踩在规划模块给出的目标落足点上。在训练阶段，落足点目标分布由一个与跟踪器竞争训练的生成模型给出。这一过程确保跟踪器在具有所需难度的环境中接受训练。由此得到的跟踪器能够克服比以往方法所能应对的更困难的地形。我们使用自研的动态四足机器人 Raibo 对该方法进行了验证。结果展现了动态且敏捷的运动能力：Raibo 能够在垂直墙面上奔跑、跳过 1.3 米的间隙、以每秒 4 米的速度跑过踏脚石，并在充满 30° 坡道、楼梯和各种尺寸箱体的地形上自主导航。
英文摘要：
High-speed legged navigation in discrete and geometrically complex environments is a challenging task because of the high-degree-of-freedom dynamics and long-horizon, nonconvex nature of the optimization problem. In this work, we propose a hierarchical navigation pipeline for legged robots that can traverse such environments at high speed. The proposed pipeline consists of a planner and tracker module. The planner module finds physically feasible foothold plans by sampling-based optimization with fast sequential filtering using heuristics and a neural network. Subsequently, rollouts are performed in a physics simulation to identify the best foothold plan regarding the engineered cost function and to confirm its physical consistency. This hierarchical planning module is computationally efficient and physically accurate at the same time. The tracker aims to accurately step on the target footholds from the planning module. During the training stage, the foothold target distribution is given by a generative model that is trained competitively with the tracker. This process ensures that the tracker is trained in an environment with the desired difficulty. The resulting tracker can overcome terrains that are more difficult than what the previous methods could manage. We demonstrated our approach using Raibo, our in-house dynamic quadruped robot. The results were dynamic and agile motions: Raibo is capable of running on vertical walls, jumping a 1.3-meter gap, running over stepping stones at 4 meters per second, and autonomously navigating on terrains full of 30° ramps, stairs, and boxes of various sizes.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
