Radar and stereo vision fusion for multitarget tracking on the special Euclidean group
| Autor: | Josip Cesic, Ivan Marković, Ivan Petrović, Igor Cvišić |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
Computer science
business.industry General Mathematics Euclidean group 020206 networking & telecommunications Advanced driver assistance systems 02 engineering and technology Filter (signal processing) Computer Science Applications law.invention Extended Kalman filter Control and Systems Engineering law 0202 electrical engineering electronic engineering information engineering Traffic sign recognition 020201 artificial intelligence & image processing Computer vision Artificial intelligence Radar business advanced driver assistance systems detection and tracking of moving objects joint integrated probabilistic data association radar stereo camera Software Stereo camera |
| Zdroj: | Robotics and Autonomous Systems. 83:338-348 |
| ISSN: | 0921-8890 |
| DOI: | 10.1016/j.robot.2016.05.001 |
| Popis: | Reliable scene analysis, under varying conditions, is an essential task in nearly any assistance or autonomous system application, and advanced driver assistance systems (ADAS) are no exception. ADAS commonly involve adaptive cruise control, collision avoidance, lane change assistance, traffic sign recognition, and parking assistance-with the ultimate goal of producing a fully autonomous vehicle. The present paper addresses detection and tracking of moving objects within the context of ADAS. We use a multisensor setup consisting of a radar and a stereo camera mounted on top of a vehicle. We propose to model the sensors uncertainty in polar coordinates on Lie Groups and perform the objects state filtering on Lie groups, specifically, on the product of two special Euclidean groups, i.e., SE ( 2 ) 2 . To this end, we derive the designed filter within the framework of the extended Kalman filter on Lie groups. We assert that the proposed approach results with more accurate uncertainty modeling, since used sensors exhibit contrasting measurement uncertainty characteristics and the predicted target motions result with banana-shaped uncertainty contours. We believe that accurate uncertainty modeling is an important ADAS topic, especially when safety applications are concerned. To solve the multitarget tracking problem, we use the joint integrated probabilistic data association filter and present necessary modifications in order to use it on Lie groups. The proposed approach is tested on a real-world dataset collected with the described multisensor setup in urban traffic scenarios. Radar and stereo camera integration for tracking in ADAS.Detection and tracking of moving objects by filtering on matrix Lie groups.State space formed as a product of two special Euclidean groups.Employed banana-shaped uncertainties typical for range-bearing sensors and vehicles in motion.JIPDA filter for multitarget tracking on matrix Lie groups. |
| Databáze: | OpenAIRE |
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