6 papers · 1 filter
Tracing Energy Flow: Learning Tactile-based Grasping Force Control to Reduce Slippage in Dynamic Object Interaction
Cheng-Yu Kuo, Hirofumi Shin, Takamitsu Matsubara
Regulating grasping force to reduce slippage during dynamic object interaction remains a fundamental challenge in robotic manipulation, especially when objects are manipulated by m…
ASBI: Leveraging Informative Real-World Data for Active Black-Box Simulator Tuning
Gahee Kim, Takamitsu Matsubara
Black-box simulators are widely used in robotics, but optimizing their parameters remains challenging due to inaccessible likelihoods. Simulation-Based Inference (SBI) tackles this…
Prolonging Tool Life: Learning Skillful Use of General-purpose Tools through Lifespan-guided Reinforcement Learning
Po-Yen Wu, Cheng-Yu Kuo, Yuki Kadokawa +1
In inaccessible environments with uncertain task demands, robots often rely on general-purpose tools that lack predefined usage strategies. These tools are not tailored for particu…
Where Do Humans Look When Demonstrating to Robots? Human Gaze Behavior in Pick-and-Place Tasks Across Demonstration Devices
Yutaro Ishida, Takamitsu Matsubara, Takayuki Kanai +2
Imitation learning for generalizable performance often requires a large volume of demonstration data, making the process significantly costly. One promising strategy to address thi…
KeyMPs: One-Shot Vision-Language Guided Motion Generation by Sequencing DMPs for Occlusion-Rich Tasks
Edgar Anarossi, Yuhwan Kwon, Hirotaka Tahara +6
Dynamic Movement Primitives (DMPs) provide a flexible framework wherein smooth robotic motions are encoded into modular parameters. However, they face challenges in integrating mul…
BEAC: Imitating Complex Exploration and Task-oriented Behaviors for Invisible Object Nonprehensile Manipulation
Hirotaka Tahara, Takamitsu Matsubara
Applying imitation learning (IL) is challenging to nonprehensile manipulation tasks of invisible objects with partial observations, such as excavating buried rocks. The demonstrato…