37 citations · 121 across the 7 of their papers we have counts for
7 papers
TACT: Humanoid Whole-body Contact Manipulation through Deep Imitation Learning with Tactile Modality
Masaki Murooka, Takahiro Hoshi, Kensuke Fukumitsu +5
Manipulation with whole-body contact by humanoid robots offers distinct advantages, including enhanced stability and reduced load. On the other hand, we need to address challenges…
Humanoid Loco-Manipulations Pattern Generation and Stabilization Control
Masaki Murooka, Kevin Chappellet, Arnaud Tanguy +5
In order for a humanoid robot to perform loco-manipulation such as moving an object while walking, it is necessary to account for sustained or alternating external forces other tha…
Humanoid Loco-manipulation Planning based on Graph Search and Reachability Maps
Masaki Murooka, Iori Kumagai, Mitsuharu Morisawa +2
In this letter, we propose an efficient and highly versatile loco-manipulation planning for humanoid robots. Loco-manipulation planning is a key technological brick enabling humano…
Centroidal Trajectory Generation and Stabilization based on Preview Control for Humanoid Multi-contact Motion
Masaki Murooka, Mitsuharu Morisawa, Fumio Kanehiro
Multi-contact motion is important for humanoid robots to work in various environments. We propose a centroidal online trajectory generation and stabilization control for humanoid d…
Whole-body Multi-contact Motion Control for Humanoid Robots Based on Distributed Tactile Sensors
Masaki Murooka, Kensuke Fukumitsu, Marwan Hamze +4
To enable humanoid robots to work robustly in confined environments, multi-contact motion that makes contacts not only at extremities, such as hands and feet, but also at intermedi…
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…