193 citations · 233 across the 8 of their papers we have counts for
4 papers · 1 filter
Benchmarking Potential Based Rewards for Learning Humanoid Locomotion
Se Hwan Jeon, Steve Heim, Charles Khazoom +1
The main challenge in developing effective reinforcement learning (RL) pipelines is often the design and tuning the reward functions. Well-designed shaping reward can lead to signi…
Learning Fast and Precise Pixel-to-Torque Control
Steffen Bleher, Steve Heim, Sebastian Trimpe
In the field, robots often need to operate in unknown and unstructured environments, where accurate sensing and state estimation (SE) becomes a major challenge. Cameras have been u…
An Open Torque-Controlled Modular Robot Architecture for Legged Locomotion Research
Felix Grimminger, Avadesh Meduri, Majid Khadiv +10
We present a new open-source torque-controlled legged robot system, with a low-cost and low-complexity actuator module at its core. It consists of a high-torque brushless DC motor…
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…