2 papers
cs.RO2024
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…
cs.RO2024
CLIP feature-based randomized control using images and text for multiple tasks and robots
Kazuki Shibata, Hideki Deguchi, Shun Taguchi
This study presents a control framework leveraging vision language models (VLMs) for multiple tasks and robots. Notably, existing control methods using VLMs have achieved high perf…