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Junnosuke Kamohara

2 accepted papers

2026

RL-Augmented Adaptive Model Predictive Control for Bipedal Locomotion Over Challenging Terrain

ICRA 2026poster

Model predictive control (MPC) has demonstrated effectiveness for humanoid bipedal locomotion; however, its applicability in challenging environments, such as rough and slippery terrain, is limited by the difficulty of modeling terrain interactions. In contrast, reinforcement learning (RL) has achie…

2024

OmniLRS: A Photorealistic Simulator for Lunar Robotics

ICRA 2024poster

Developing algorithms for extra-terrestrial robotic exploration has always been challenging. Along with the complexity associated with these environments, one of the main issues remains the evaluation of said algorithms. With the regained interest in lunar exploration, there is also a demand for qua…

Cited by 12SourcecodeScholar