Autonomous pallet localization and picking for industrial forklifts: a robust range and look method

Abstract

A combined double-sensor architecture, laser and camera, and a new algorithm named RLPF are presented as a solution to the problem of identifying and localizing a pallet, the position and angle of which are a priori known with large uncertainty. Solving this task for autonomous robot forklifts is of great value for logistics industry. The state-of-the-art is described to show how our approach overcomes the limitations of using either laser ranging or vision. An extensive experimental campaign and uncertainty analysis are presented. For the docking task, new dynamic nonlinear path planning which takes into account vehicle dynamics is proposed.