Adaptive Path Planning for Autonomous Mobile Robots in Dynamic Warehouse Environments

Abstract

Autonomous Mobile Robots (AMRs) in logistics often face dynamic obstacles such as human workers and forklifts. We introduce a hybrid path planning algorithm combining global D* Lite with local dynamic window approaches. The proposed system re-routes in real-time without stopping, increasing overall warehouse throughput by 12% during peak hours.