Accurate, precise and robust motion control of dynamic quadrupedal walking robots.

Dynamic quadrupedal walking robots have many potential applications because their legs let them achieve superior mobility and agility relative to wheels. These autonomous machines have the capability to perform various tasks that are deemed too dangerous for or unachievable by humans. They can be sent to assess disaster sites, rescue a life, dispose of dangerous goods, carry unwieldy loads or carry out an inspection-in unfavourable environments or challenging conditions. This functionality has a significant social value and the mature version of this technology will be acquired by applicable large-scale private and public organisations.
Four-legged robots have seen a major interest from other world-leading universities, institutions and companies. The IIT in a partnership with Moog Inc. built the HyQ2Max robot. Boston Dynamics, a spin-off from the MIT, constructed several similar products including BigDog and SpotMini. ANYbotics, a spin-off from the ETH, developed ANYmal; a version of this robot is available to the Dynamic Robot Systems group at the University of Oxford and will be the focus of this research project.
The legs of this versatile machine are driven by twelve electric motors mounted at the joints to facilitate whole-body control techniques enabling dynamic manoeuvres such as jumping or running. The kinematic structure of the robot is designed to achieve large mobility allowing it to overcome obstacles and stairs.
Significant amount of research is focused on periodic gaits. However, a truly dynamic robot needs to be able to traverse complex topologies and reject unforeseen external impulsive load disturbances autonomously and in real-time. The aim of the project is to develop low-level motion control algorithms which will intelligently stiffen and relax the legs of the robot to either stabilise its stance effectively or allow it to execute demanding motion plans while maintaining balance.
We will explore simple, cascaded PID control and rely on torque measurements. The use of a full-state feedback could potentially improve the controllability of the joints. The addition of a nonlinear extended state observer, which is derived from active disturbance rejection control, to compensate for the combined disturbances would make the robot inherently more robust. While these approaches have been discussed extensively in peer-reviewed literature, applying them to a real, sophisticated, four-legged robotic system with twelve motors is a source of originality.
In 2018, Winkler et al. proposed to generate feasible motion plans via trajectory optimisation without imposing a fixed gait sequence or foothold location. Instead a nonlinear solver iteratively determines what set of parameters and decisions will yield a successful course of motion. While promising, this mainly theoretical idea was not sufficiently tested in experiment. It also relies on certain assumptions and simplifications of the physical model which deviate from the real world. Building upon this method would result in a novel approach to dynamic motion.
This project falls within the EPSRC Engineering research area. The research is supported by ANYbotics and Moog Inc.

Reference:
A Winkler, D Bellicoso, M Hutter, J Buchli. Gait and Trajectory Optimization for Legged Systems through Phase-based End-Effector Parameterization. IEEE Robotics and Automation Letters (RA-L) 3, 1560-1567