3 citations · 5 across the 4 of their papers we have counts for
4 papers
GenCAD-Self-Repairing: Feasibility Enhancement for 3D CAD Generation
Chikaha Tsuji, Enrique Flores Medina, Harshit Gupta +1
With the advancement of generative AI, research on its application to 3D model generation has gained traction, particularly in automating the creation of Computer-Aided Design (CAD…
Adaptive Wiping: Adaptive contact-rich manipulation through few-shot imitation learning with Force-Torque feedback and pre-trained object representations
Chikaha Tsuji, Enrique Coronado, Pablo Osorio +1
Imitation learning offers a pathway for robots to perform repetitive tasks, allowing humans to focus on more engaging and meaningful activities. However, challenges arise from the…
TRAIL Team Description Paper for RoboCup@Home 2023
Chikaha Tsuji, Dai Komukai, Mimo Shirasaka +13
Our team, TRAIL, consists of AI/ML laboratory members from The University of Tokyo. We leverage our extensive research experience in state-of-the-art machine learning to build gene…
Self-Recovery Prompting: Promptable General Purpose Service Robot System with Foundation Models and Self-Recovery
Mimo Shirasaka, Tatsuya Matsushima, Soshi Tsunashima +8
A general-purpose service robot (GPSR), which can execute diverse tasks in various environments, requires a system with high generalizability and adaptability to tasks and environm…