In emerging autonomous vehicles, perception of the environment around the vehicle depends not only on the quality and choice of sensor type, but more importantly also on the instrumented location and orientation of each of the sensors. This chapter explores the synthesis of heterogeneous sensor configurations towards achieving vehicle autonomy goals. We propose a novel optimization framework called VESPA that explores the design space of sensor placement locations and orientations to find the optimal sensor configuration for a vehicle. We demonstrate how our framework can obtain optimal sensor configurations for heterogeneous sensors deployed across two contemporary real vehicles.
Sensing Optimization in Automotive Platforms
Machine Learning and Optimization Techniques for Automotive Cyber-Physical Systems ; Kapitel : 19 ; 545-563
2023-09-02
19 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
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