1.5k citations · 2.3k across the 9 of their papers we have counts for
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Learning to walk in confined spaces using 3D representation
Takahiro Miki, Joonho Lee, Lorenz Wellhausen +1
Legged robots have the potential to traverse complex terrain and access confined spaces beyond the reach of traditional platforms thanks to their ability to carefully select footho…
Solving Multi-Entity Robotic Problems Using Permutation Invariant Neural Networks
Tianxu An, Joonho Lee, Marko Bjelonic +2
Challenges in real-world robotic applications often stem from managing multiple, dynamically varying entities such as neighboring robots, manipulable objects, and navigation goals.…
Evaluation of Constrained Reinforcement Learning Algorithms for Legged Locomotion
Joonho Lee, Lukas Schroth, Victor Klemm +3
Shifting from traditional control strategies to Deep Reinforcement Learning (RL) for legged robots poses inherent challenges, especially when addressing real-world physical constra…
Learning-based Design and Control for Quadrupedal Robots with Parallel-Elastic Actuators
Filip Bjelonic, Joonho Lee, Philip Arm +4
Parallel-elastic joints can improve the efficiency and strength of robots by assisting the actuators with additional torques. For these benefits to be realized, a spring needs to b…
Learning robust perceptive locomotion for quadrupedal robots in the wild
Takahiro Miki, Joonho Lee, Jemin Hwangbo +3
Legged robots that can operate autonomously in remote and hazardous environments will greatly increase opportunities for exploration into under-explored areas. Exteroceptive percep…
CERBERUS: Autonomous Legged and Aerial Robotic Exploration in the Tunnel and Urban Circuits of the DARPA Subterranean Challenge
Marco Tranzatto, Frank Mascarich, Lukas Bernreiter +38
Autonomous exploration of subterranean environments constitutes a major frontier for robotic systems as underground settings present key challenges that can render robot autonomy h…