156 citations · 246 across the 43 of their papers we have counts for
6 papers · 1 filter
Cutting Sequence Diffuser: Sim-to-Real Transferable Planning for Object Shaping by Grinding
Takumi Hachimine, Jun Morimoto, Takamitsu Matsubara
Automating object shaping by grinding with a robot is a crucial industrial process that involves removing material with a rotating grinding belt. This process generates removal res…
Cooperative Grasping and Transportation using Multi-agent Reinforcement Learning with Ternary Force Representation
Ing-Sheng Bernard-Tiong, Yoshihisa Tsurumine, Ryosuke Sota +2
Cooperative grasping and transportation require effective coordination to complete the task. This study focuses on the approach leveraging force-sensing feedback, where robots use…
Robust Iterative Value Conversion: Deep Reinforcement Learning for Neurochip-driven Edge Robots
Yuki Kadokawa, Tomohito Kodera, Yoshihisa Tsurumine +2
A neurochip is a device that reproduces the signal processing mechanisms of brain neurons and calculates Spiking Neural Networks (SNNs) with low power consumption and at high speed…
Unsupervised Neural Motion Retargeting for Humanoid Teleoperation
Satoshi Yagi, Mitsunori Tada, Eiji Uchibe +3
This study proposes an approach to human-to-humanoid teleoperation using GAN-based online motion retargeting, which obviates the need for the construction of pairwise datasets to i…
Leveraging Demonstrator-perceived Precision for Safe Interactive Imitation Learning of Clearance-limited Tasks
Hanbit Oh, Takamitsu Matsubara
Interactive imitation learning is an efficient, model-free method through which a robot can learn a task by repetitively iterating an execution of a learning policy and a data coll…
Incipient Slip Detection by Vibration Injection into Soft Sensor
Naoto Komeno, Takamitsu Matsubara
In robotic manipulation, preventing objects from slipping and establishing a secure grip on them is critical. Successful manipulation requires tactile sensors that detect the micro…