Vijayakumar, Sethu

Li, Zhibin

Mistry, Michael

Ferrolho, Henrique Manuel Martins

2022-09-30T09:19:43Z

2022-09-30T09:19:43Z

2022-09-30

In robotics, robustness is an important and desirable attribute of any system, from perception to planning and control. Robotic systems need to handle numerous factors of uncertainty when they are deployed, and the more robust a method is, the fewer chances there are of something going wrong. In planning and control, being robust is crucial to deal with uncertain contact timings and positions, mismatches in the dynamics model of the system, noise in the sensor readings and communication delays. In this thesis, we focus on the problem of dealing with uncertainty and external disturbances applied to the robot. Reactive robustness can be achieved at the control stage using a variety of control schemes. For example, model predictive control approaches are robust against external disturbances thanks to the online high-frequency replanning of the motion being executed. However, taking robustness into account in a proactive way, i.e., during the planning stage itself, enables the adoption of kinematic configurations that allow the system as a whole to better deal with uncertainty and disturbances. To this end, we propose a novel trajectory optimisation framework for robotic systems, ranging from fixed-base manipulators to legged robots, such as humanoids or quadrupeds equipped with arms. We tackle the problem from a first-principles perspective, and define a robustness metric based on the robot’s capabilities, such as the torques available to the system (considering actuator torque limits) and contact stability constraints. We compare our results with other existing approaches and, through simulation and experiments on the real robot, we show that our method is able to plan trajectories that are more robust against external disturbances.

https://hdl.handle.net/1842/39397

http://dx.doi.org/10.7488/era/2647

en

The University of Edinburgh

H. Ferrolho, V. Ivan, W. Merkt, I. Havoutis, S. Vijayakumar. ‘RoLoMa: Robust Loco-Manipulation for Quadruped Robots with Arms’. Under review for IEEE Transactions on Robotics (T-RO), 2022

H. Ferrolho, W. Merkt, C. Tiseo, S. Vijayakumar. ‘Residual Force Polytope: Admissible Task-Space Forces of Dynamic Trajectories’. Robotics and Autonomous Systems (RAS), 2021

Y. Yang, W. Merkt, H. Ferrolho, V. Ivan, S. Vijayakumar. ‘Efficient Humanoid Motion Planning on Uneven Terrain Using Paired Forward-Inverse Dynamic Reachability Maps’. In IEEE Robotics and Automation Letters (RA-L), 2017

H. Ferrolho, V. Ivan, W. Merkt, I. Havoutis, S. Vijayakumar. ‘Inverse Dynamics vs. Forward Dynamics in Direct Transcription Formulations for Trajectory Optimization’. In IEEE International Conference on Robotics and Automation (ICRA), Xi’an, China, 2021

H. Ferrolho, W. Merkt, V. Ivan, W. Wolfslag, S. Vijayakumar. ‘Optimizing Dynamic Trajectories for Robustness to Disturbances Using Polytopic Projections’. In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Las Vegas, USA, 2020

H. Ferrolho, W. Merkt, Y. Yang, V. Ivan, S. Vijayakumar. ‘Whole-Body End-Pose Planning for Legged Robots on Inclined Support Surfaces in Complex Environments’. In Proceedings of IEEE-RAS International Conference on Humanoid Robots (Humanoids), Beijing, China, 2018.

Henrique Ferrolho and contributors. TORA.jl. 2020. url: https://github.com/ JuliaRobotics/TORA.jl

robotic system robustness

uncertainty

reactive robustness

predictive control

legged robots

fixed-base manipulators

external disturbances

Robustness to external disturbances for legged robots using dynamic trajectory optimisation

Thesis or Dissertation

Doctoral

PhD Doctor of Philosophy