VESPA: A Framework for Optimizing Heterogeneous Sensor Placement and Orientation for Autonomous Vehicles

Abstract

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 article explores the synthesis of heterogeneous sensor configurations toward achieving vehicle autonomy goals. We propose a novel optimization framework called VESPA that explores the design space of the 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.