High-speed control and navigation for quadrupedal robots on complex and discrete terrain

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. One-Sentence Summary: A framework for legged navigation, which enables high-speed running on complex and discrete terrain. 1 Introduction With recent advances in robotic technology, there has been an increase in efforts to replace humans with robots in certain workplaces. In particular, legged robots are promising candidates to replace humans in search and rescue missions at disaster sites and construction areas because of their ability to efficiently traverse various challenging terrains. Rapid exploration and extensive area coverage are paramount for these missions. However, rapid locomotion in such environments, which consist of discontinuous terrains such as stairs, steps, large debris, and gaps, is still challenging for legged robots. These tasks require not only a controller capable of generating highly dynamic motions but also a fast and dynamically consistent navigation algorithm, both of which are still challenging to develop. T o swiftly navigate discontinuous terrains, finding a feasible foothold plan for the given environment and coordinating all joint actuators to track the foothold plan precisely are crucial.