Showing cs.ROShow all
3 papers · 1 filter
cs.RO2026
Amortising Trajectory Optimisation for Residual MPC via Implicit Contact Differentiation
Daniel Layeghi, Thomas Corbères, Calum Arnott +4
Differentiable simulation can accelerate contact-rich trajectory optimisation by exposing local sensitivities of task outcomes to controls. Existing approaches either use finite di…
cs.RO2025
Learning Long-Horizon Robot Manipulation Skills via Privileged Action
Xiaofeng Mao, Yucheng Xu, Zhaole Sun +3
Long-horizon contact-rich tasks are challenging to learn with reinforcement learning, due to ineffective exploration of high-dimensional state spaces with sparse rewards. The learn…
cs.RO2023
Neural Lyapunov and Optimal Control
Daniel Layeghi, Steve Tonneau, Michael Mistry
Despite impressive results, reinforcement learning (RL) suffers from slow convergence and requires a large variety of tuning strategies. In this paper, we investigate the ability o…