Near-Range Environmental Perception for Inland Waterway Vessels: A Comparative Study of LiDAR and Automotive FMCW RADAR Sensors
| Autor: | Herrmann, R., Bose, S., Filip, I., Medina, D., Ziebold, R., Gehrig, S., Lenhard, T., Gardill, M. |
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| Rok vydání: | 2024 |
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| Druh dokumentu: | Working Paper |
| Popis: | Advancing towards high automation and autonomous operations is crucial for the future of inland waterway transport (IWT) systems. These systems necessitate robust and precise onboard sensory technologies that can perceive the environment under all weather conditions, including static features for local positioning techniques such as Simultaneous Localization and Mapping (SLAM). Traditional marine RADAR, mandatory on vessels and operating in the 9300-9500 MHz frequency band, can cover ranges from 15 to 1200 meters but are inadequate for detecting closer objects, making them unsuitable for automated docking maneuvers, lock entry, or bridge undercrossings. This necessitates the development of reliable close-range sensor technology that functions effectively in all weather conditions. In present research works on vessel automation, LiDAR sensors, operating in the nearinfrared range, are used predominantly to detect the immediate surroundings of vessels but suffer significant degradation in poor visibility. Conversely, automotive RADAR sensors, utilizing the 76-81 GHz frequency band, can detect objects from a few centimeters to up to 200 meters, even in adverse conditions. These sensors are commonly used in advanced autonomous road traffic systems and are evaluated in this study for their suitability in inland navigation and maneuvering. This paper discusses a distributed sensor network of four compact automotive frequencymodulated continuous-wave (FMCW) radars mounted on a cabin boat as a test platform. Initial field experiments demonstrate the RADAR network's ability to perceive closerange static environmental features around the boat in inland waters. The paper also provides a comparative analysis of the environmental detection capabilities of automotive RADAR and LiDAR sensors. Comment: 9 pages, 11 figues, conference, included in conference proceedings of DGON POSNAV 2024 |
| Databáze: | arXiv |
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