Robust Continuous System Integration for Critical Deep-Sea Robot Operations Using Knowledge-Enabled Simulation in the Loop
| Autor: | Mueller, Christian A., Doernbach, Tobias, Chavez, Arturo Gomez, Koehntopp, Daniel, Birk, Andreas |
|---|---|
| Rok vydání: | 2018 |
| Předmět: | |
| Zdroj: | IEEE/RSJ International Conference on Intelligent Robots and Systems (2018) 1892-1899 |
| Druh dokumentu: | Working Paper |
| DOI: | 10.1109/IROS.2018.8594392 |
| Popis: | Deep-sea robot operations demand a high level of safety, efficiency and reliability. As a consequence, measures within the development stage have to be implemented to extensively evaluate and benchmark system components ranging from data acquisition, perception and localization to control. We present an approach based on high-fidelity simulation that embeds spatial and environmental conditions from recorded real-world data. This simulation in the loop (SIL) methodology allows for mitigating the discrepancy between simulation and real-world conditions, e.g. regarding sensor noise. As a result, this work provides a platform to thoroughly investigate and benchmark behaviors of system components concurrently under real and simulated conditions. The conducted evaluation shows the benefit of the proposed work in tasks related to perception and self-localization under changing spatial and environmental conditions. Comment: published on IROS 2018 |
| Databáze: | arXiv |
| Externí odkaz: |
|