Trabajo presentado a la IEEE Conference on Roboticand Automation (ICRA), celebrada en Estocolmo (Suecia) del 16 al 21 de mayo de 2016. ; Localization is the key perceptual process closing the loop of autonomous navigation, allowing self-driving vehi- cles to operate in a deliberate way. To ensure robust localization, autonomous vehicles have to implement redundant estimation processes, ideally independent in terms of the underlying physics behind sensing principles. This paper presents a stereo radar odometry system, which can be used as such a redundant system, complementary to other odometry estimation processes, providing robustness for long-term operability. The presented work is novel with respect to previously published methods in that it contains: (i) a detailed formulation of the Doppler error and its associated uncertainty; (ii) an observability analysis that gives the minimal conditions to infer a 2D twist from radar readings; and (iii) a numerical analysis for optimal vehicle sensor placement. Experimental results are also detailed that validate the theoretical insights. ; This work was supported by the EU Project CargoAnts: Cargo Handling by Automated Next Generation Transportation Systems for Ports and Terminals (FP7-SST-2013-RTD-1-605598). ; Peer Reviewed
Observability analysis and optimal sensor placement in stereo radar odometry
2016-01-01
Conference paper
Electronic Resource
English
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