Legged robots are capable of navigating rough terrain, but have traditionally been restricted to slow speeds. New robots combine the power density necessary for rapid motions with increasingly sophisticated leg designs. Developing controllers that effectively coordinate these high-DOF legs to generate fast, agile motions is challenging. In this paper we examine a pair of control approaches to generate high-speed trotting for the direct-drive quadruped robot Minitaur. We first show that optimization of a redesigned feed-forward trajectory improves the robot’s running speed by 45%, from 1.52m/s to 1.93m/s. We then utilize a monopod version of Minitaur’s 5-bar leg to directly compare this control approach to a dynamic, model-based strategy. We find gaits with the optimized trajectory are able to achieve speeds up to 2.44m/s, but the model-based dynamic controller is able to find gaits that are more robust to parameter changes, nearly as fast, and up to 70% more efficient.
|