6 papers
Model Predictive Path Integral PID Control for Learning-Based Path Following
Teruki Kato, Koshi Oishi, Seigo Ito
Classical proportional--integral--derivative (PID) control remains widely used in industrial control systems, while model predictive control (MPC) is actively studied to achieve hi…
Visual-Based Forklift Learning System Enabling Zero-Shot Sim2Real Without Real-World Data
Koshi Oishi, Teruki Kato, Hiroya Makino +1
Forklifts are used extensively in various industrial settings and are in high demand for automation. In particular, counterbalance forklifts are highly versatile and employed in di…
Imitation-regularized Optimal Transport on Networks: Provable Robustness and Application to Logistics Planning
Koshi Oishi, Yota Hashizume, Tomohiko Jimbo +2
Transport systems on networks are crucial in various applications, but face a significant risk of being adversely affected by unforeseen circumstances such as disasters. The applic…
Scratch Team of Single-Rotor Robots and Decentralized Cooperative Transportation with Robot Failure
Koshi Oishi, Yasushi Amano, Jimbo Tomohiko
Achieving cooperative transportation by aerial robot teams ensures flexibility regarding payloads and robustness against failures, which has garnered significant attention in recen…
Cooperative Transportation using Multiple Single-Rotor Robots and Decentralized Control for Unknown Payloads
Koshi Oishi, Yasushi Amano, Tomohiko Jimbo
Cooperative transportation via multiple aerial robots has the potential to support various payloads and reduce the chances of them being dropped. Furthermore, autonomously controll…
Autonomous Cooperative Transportation System involving Multi-Aerial Robots with Variable Attachment Mechanism
Koshi Oishi, Tomohiko Jimbo
Cooperative transportation by multi-aerial robots has the potential to support various payloads and improve failsafe against dropping. Furthermore, changing the attachment position…