Towards automatic discovery of agile gaits for quadrupedal robots

Abstract

Abstract-Developing control methods that allow legged robots to move with skill and agility remains one of the grand challenges in robotics. In order to achieve this ambitious goal, legged robots must possess a wide repertoire of motor skills. A scalable control architecture that can represent a variety of gaits in a unified manner is therefore desirable. Inspired by the motor learning principles observed in nature, we use an optimization approach to automatically discover and fine-tune parameters for agile gaits. The success of our approach is due to the controller parameterization we employ, which is compact yet flexible, therefore lending itself well to learning through repetition. We use our method to implement a flying trot, a bound and a pronking gait for StarlETH, a fully autonomous quadrupedal robot.

Concurrent Optimization of Mechanical Design and Locomotion Control of a Legged Robot

“…While this is always a concern, given that we have been able to use parameters optimized in simulation on our robot in the past, 8 we believe the results of the simulations are trustworthy. What we found very important is to consider the effect of sensor noise.…”

“…8 The foothold locations are regulated using simple controllers based on an inverted pendulum that keep the robot balanced. The limb coordination and the timings of the swing and stance phases of the legs are parameterized based on the anteroposterior sequence of movement (APS) theory proposed by Abourachid et al 12 This parameterization, as shown in Fig.…”

“…In previous work, 8 we optimized the parameters of a robust locomotion controller 9 for an electrically-driven medium-dog-sized quadrupedal robot called StarlETH. 10 The optimization approach allowed us to find control parameters for two agile gaits, the pronk and the bound, which were too difficult to find manually a .…”

Direct state-to-action mapping for high DOF robots using ELM

“…We use the optimization framework used in [22]. The framework is rollout-based and requires many forward simulation of the dynamics.…”

Dynamic trotting on slopes for quadrupedal robots

“…The control method can cope with limited sensory information and leads to a large number of gaits, such as forward and lateral walks, trot, pronk and bound as shown in [15]. The controllers are robust against unanticipated perturbations caused by pushes or irregular terrain, but they fail on unperceived slopes larger than 5…”