5 citations · 29 across the 23 of their papers we have counts for
5 papers · 1 filter
A Differentiable Newton-Euler Algorithm for Real-World Robotics
Michael Lutter, Johannes Silberbauer, Joe Watson +1
Obtaining dynamics models is essential for robotics to achieve accurate model-based controllers and simulators for planning. The dynamics models are typically obtained using model…
Real Robot Challenge: A Robotics Competition in the Cloud
Stefan Bauer, Felix Widmaier, Manuel Wüthrich +39
Dexterous manipulation remains an open problem in robotics. To coordinate efforts of the research community towards tackling this problem, we propose a shared benchmark. We designe…
Efficient Stochastic Optimal Control through Approximate Bayesian Input Inference
Joe Watson, Hany Abdulsamad, Rolf Findeisen +1
Optimal control under uncertainty is a prevailing challenge for many reasons. One of the critical difficulties lies in producing tractable solutions for the underlying stochastic o…
Benchmarking Structured Policies and Policy Optimization for Real-World Dexterous Object Manipulation
Niklas Funk, Charles Schaff, Rishabh Madan +10
Dexterous manipulation is a challenging and important problem in robotics. While data-driven methods are a promising approach, current benchmarks require simulation or extensive en…
Advancing Trajectory Optimization with Approximate Inference: Exploration, Covariance Control and Adaptive Risk
Joe Watson, Jan Peters
Discrete-time stochastic optimal control remains a challenging problem for general, nonlinear systems under significant uncertainty, with practical solvers typically relying on the…