Abstract The ongoing automation of manufacturing processes increases productivity and reduces physically demanding labor, a cornerstone for today’s living standards and economic wealth in industrialized countries. However, industrial automation requires a costly setup phase. Therefore, it is only worthwhile when manufacturing large quantities of identical products. As globalization increases the pace of market changes and due to the trend towards product customization, there is a demand for more flexible, adaptable automation to retain global competitiveness for smaller batch sizes and changing products. Here, autonomous navigation is a key technology to reduce setup costs and increase flexibility. In this thesis, we present contributions towards the deployment of mobile robot naviga- tion in real-world industrial settings. We provide vehicle-based material transport between processes that is fast and intuitive to set up. Since our approaches only rely on wheel encoders and the mandatory safety scanners of an autonomous vehicle, they work without additional, inflexible infrastructure. We first propose a navigation system that enables omnidirectional vehicles to autonomously navigate with high accuracy while respecting safety constraints. Our system accounts for the dynamics of the vehicle when optimiz- ing smooth, curvature continuous trajectories that are frequently updated in changing environments. We furthermore present a localization and docking method to achieve millimeter accuracy at target locations. For use cases that require automated vehicles to follow predefined routes, we propose an approach for intuitive instruction that relies on user demonstrations and can be combined with our navigation system to realize different levels of autonomy. For scenarios with predefined routes only, we further reduce the setup costs. Our teach-and-repeat framework needs no pre-built environment map and only a single, non-expert demonstration to track taught trajectories with millimeter accuracy. For realistic estimates of the performance and reliability of navigation systems, we propose a benchmark protocol that instead of individual components evaluates complete systems. The tested system and a reference system interact with a carefully specified and scripted dynamic environment to ensure comparability between different evaluations. We conducted extensive experiments for all our systems. Through the combination of high accuracy and reliability with flexibility and ease of use, they present a substantial contribution towards navigation for flexible automation. Autonomous vehicles can also be equipped with robotic arms, e.g., welding robots mounted on autonomous vehicles instead of bolted to the factory floor. Beyond logistics, navigation can thereby contribute to efficiently reconfigurable process chains and the vision of transformable factories.
@phdthesis{sprunk15phd,
author = {Christoph Sprunk},
title = {Highly Accurate Mobile Robot Navigation},
school = {Albert-Ludwigs-University of Freiburg, Department of Computer Science},
year = 2015,
month = nov
}