20 citations · 23 across the 3 of their papers we have counts for
3 papers
cs.AI2018★ 1 cited
Learning from Outside the Viability Kernel: Why we Should Build Robots that can Fall with Grace
Steve Heim, Alexander Spröwitz
Despite impressive results using reinforcement learning to solve complex problems from scratch, in robotics this has still been largely limited to model-based learning with very in…
cs.RO2018★ 20 cited
Beyond Basins of Attraction: Quantifying Robustness of Natural Dynamics
Steve Heim, Alexander Spröwitz
Properly designing a system to exhibit favorable natural dynamics can greatly simplify designing or learning the control policy. However, it is still unclear what constitutes favor…
cs.RO2017★ 2 cited
Shaping in Practice: Training Wheels to Learn Fast Hopping Directly in Hardware
Steve Heim, Felix Ruppert, Alborz A. Sarvestani +1
Learning instead of designing robot controllers can greatly reduce engineering effort required, while also emphasizing robustness. Despite considerable progress in simulation, appl…