Computational Complexity of Terrain Mapping Perception in Autonomous Mobility

Abstract

For autonomously navigating vehicles, the automatic generation of dense geometric models of the environment is a computationally expensive process. Using first principles, it is possible to quantify the relationship between the raw throughput required of the perception system and the maximum safely achievable speed of the vehicle. We show that terrain mapping perception is of polynomial complexity in the response distance. To the degree that geometric perception consumes time, it also degrades real-time response characteristics. Given this relationship, several strategies of adaptive geometric perception arise which are practical for autonomous vehicles.