ICP-Based Pallet Tracking for Unloading on Inclined Surfaces by Autonomous Forklifts

TL;DR

This paper introduces an ICP-based control method enabling autonomous forklifts to unload pallets on inclined surfaces without dragging, by real-time tracking and alignment of the fork relative to the pallet.

Contribution

It presents a novel ICP-based approach for real-time pallet tracking and alignment on inclined surfaces, improving unloading safety and efficiency.

Findings

Successful real-time pallet tracking using ICP algorithm.

Effective fork alignment parallel to inclined surfaces.

Validated method through simulations and real forklift experiments.

Abstract

This paper proposes a control method for autonomous forklifts to unload pallets on inclined surfaces, enabling the fork to be withdrawn without dragging the pallets. The proposed method applies the Iterative Closest Point (ICP) algorithm to point clouds measured from the upper region of the pallet and thereby tracks the relative position and attitude angle difference between the pallet and the fork during the unloading operation in real-time. According to the tracking result, the fork is aligned parallel to the target surface. After the fork is aligned, it is possible to complete the unloading process by withdrawing the fork along the tilt, preventing any dragging of the pallet. The effectiveness of the proposed method is verified through dynamic simulations and experiments using a real forklift that replicate unloading operations onto the inclined bed of a truck.