3 papers
eess.SY2026
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…
cs.MA2025
MAPF-HD: Multi-Agent Path Finding in High-Density Environments
Hiroya Makino, Seigo Ito
Multi-agent path finding (MAPF) involves planning efficient paths for multiple agents to move simultaneously while avoiding collisions. In typical warehouse environments, agents ar…
cs.RO2025
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…