1 citations · 1 across the 3 of their papers we have counts for
3 papers · 1 filter
Real-World Fluid Directed Rigid Body Control via Deep Reinforcement Learning
Mohak Bhardwaj, Thomas Lampe, Michael Neunert +6
Recent advances in real-world applications of reinforcement learning (RL) have relied on the ability to accurately simulate systems at scale. However, domains such as fluid dynamic…
A Whole-Body Software Abstraction layer for Control Design of free-floating Mechanical Systems
Francesco Romano, Silvio Traversaro, Daniele Pucci +3
In this paper, we propose a software abstraction layer to simplify the design and synthesis of whole-body controllers without making any preliminary assumptions on the control law…
Prioritized Optimal Control
Andrea Del Prete, Francesco Romano, Lorenzo Natale +3
This paper presents a new technique to control highly redundant mechanical systems, such as humanoid robots. We take inspiration from two approaches. Prioritized control is a wides…