35 citations · 54 across the 7 of their papers we have counts for
7 papers
Robust Humanoid Walking on Compliant and Uneven Terrain with Deep Reinforcement Learning
Rohan P. Singh, Mitsuharu Morisawa, Mehdi Benallegue +2
For the deployment of legged robots in real-world environments, it is essential to develop robust locomotion control methods for challenging terrains that may exhibit unexpected de…
Learning Bipedal Walking for Humanoids with Current Feedback
Rohan Pratap Singh, Zhaoming Xie, Pierre Gergondet +1
Recent advances in deep reinforcement learning (RL) based techniques combined with training in simulation have offered a new approach to developing robust controllers for legged ro…
Enhanced Visual Feedback with Decoupled Viewpoint Control in Immersive Humanoid Robot Teleoperation using SLAM
Yang Chen, Leyuan Sun, Mehdi Benallegue +8
In immersive humanoid robot teleoperation, there are three main shortcomings that can alter the transparency of the visual feedback: the lag between the motion of the operator's an…
mc-mujoco: Simulating Articulated Robots with FSM Controllers in MuJoCo
Rohan P. Singh, Pierre Gergondet, Fumio Kanehiro
For safe and reliable deployment of any robot controller on the real hardware platform, it is generally a necessary practice to comprehensively assess the performance of the contro…
Instance-specific 6-DoF Object Pose Estimation from Minimal Annotations
Rohan Pratap Singh, Iori Kumagai, Antonio Gabas +3
In many robotic applications, the environment setting in which the 6-DoF pose estimation of a known, rigid object and its subsequent grasping is to be performed, remains nearly unc…
Learning Bipedal Walking On Planned Footsteps For Humanoid Robots
Rohan Pratap Singh, Mehdi Benallegue, Mitsuharu Morisawa +2
Deep reinforcement learning (RL) based controllers for legged robots have demonstrated impressive robustness for walking in different environments for several robot platforms. To e…
Rapid Pose Label Generation through Sparse Representation of Unknown Objects
Rohan Pratap Singh, Mehdi Benallegue, Yusuke Yoshiyasu +1
Deep Convolutional Neural Networks (CNNs) have been successfully deployed on robots for 6-DoF object pose estimation through visual perception. However, obtaining labeled data on a…