A Skill-Based System for Object Perception and Manipulation for Automating Kitting Tasks

Angeliki Topalidou-Kyniazopoulou
Francesco Rovida
Mikkel Rath Pedersen
Volker Krüger
Sven Behnke:
IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), Luxembourg(2015)

Abstract

The automation of kitting tasks—collecting a set of parts for one particular car into a kit—has a huge impact in the automotive industry. It considerably increases the automation levels of tasks typically conducted by human workers. Collecting the parts involves picking up objects from pallets and bins as well as placing them in the respective compartments of the kitting box. In this paper, we present a complete system for automated kitting with a mobile manipulator thereby focusing on depalletizing tasks and placing. In order to allow for low cycle times, we present particularly efficient solutions to object perception as well as motion planning and execution. For easy portability to different platforms, all components are integrated into a skill-based framework that is tightly coupled with a task planning component. We present results of experiments at both a research laboratory environment and at the industrial site of PSA Peugeot Citroen serving as a proof of concept for the overall system design and implementation.

Research Areas