RoadRunner -- Learning Traversability Estimation for Autonomous Off-road Driving

arXiv:2402.19341v1 Announce Type: cross
Abstract: Autonomous navigation at high speeds in off-road environments necessitates robots to comprehensively understand their surroundings using onboard sensing only. The extreme conditions posed by the off-road setting can cause degraded camera image quality due to poor lighting and motion blur, as well as limited sparse geometric information available from LiDAR sensing when driving at high speeds. In this work, we present RoadRunner, a novel framework capable of predicting terrain traversability and an elevation map directly …

abstract arxiv autonomous cs.cv cs.ro driving environments image lighting navigation quality roadrunner robots sensing type