82 citations · 105 across the 8 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…
Continuous-Time Fitted Value Iteration for Robust Policies
Michael Lutter, Boris Belousov, Shie Mannor +3
Solving the Hamilton-Jacobi-Bellman equation is important in many domains including control, robotics and economics. Especially for continuous control, solving this differential eq…
Learning Dynamics Models for Model Predictive Agents
Michael Lutter, Leonard Hasenclever, Arunkumar Byravan +5
Model-Based Reinforcement Learning involves learning a \textit{dynamics model} from data, and then using this model to optimise behaviour, most often with an online \textit{planner…
Robust Value Iteration for Continuous Control Tasks
Michael Lutter, Shie Mannor, Jan Peters +2
When transferring a control policy from simulation to a physical system, the policy needs to be robust to variations in the dynamics to perform well. Commonly, the optimal policy o…
Value Iteration in Continuous Actions, States and Time
Michael Lutter, Shie Mannor, Jan Peters +2
Classical value iteration approaches are not applicable to environments with continuous states and actions. For such environments, the states and actions are usually discretized, w…