Automatic Configuration of the Structure and Parameterization of Perception Pipelines

• Published in: 2019 19th International Conference on Advanced Robotics (ICAR) pp. 312 - 319
• Main Authors: Dietrich, Vincent, Kast, Bernd, Fiegert, Michael, Albrecht, Sebastian, Beetz, Michael
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.12.2019
• DOI: 10.1109/ICAR46387.2019.8981611

The configuration of perception pipelines is a complex procedure that requires substantial amounts of engineering effort and knowledge. A pipeline consists of interconnected individual perception operators and their parameters, which leads to a large configuration space of pipeline structures and parameterizations. This configuration space has to be explored efficiently in order to find a solution that fulfills the specific requirements of the target application. In this paper, we present an approach to perform automatic configuration based on structure templates and sequential model-based optimization. The structure templates allow to reduce the search space and encode prior engineering knowledge. We introduce a structure template based on hypothesis generation, hypothesis refinement, and hypothesis testing to demonstrate the effectiveness of the approach. Experimental evaluation with state-of-the-art operators is performed on data from the T-LESS dataset as well as in a real-world robotic assembly task.