Fully End-to-end Autonomous Driving with Semantic Depth Cloud Mapping and Multi-Agent. (arXiv:2204.05513v1 [cs.RO])

Focusing on the task of point-to-point navigation for an autonomous driving
vehicle, we propose a novel deep learning model trained with end-to-end and
multi-task learning manners to perform both perception and control tasks
simultaneously. The model is used to drive the ego vehicle safely by following
a sequence of routes defined by the global planner. The perception part of the
model is used to encode high-dimensional observation data provided by an RGBD
camera while performing semantic segmentation, semantic depth cloud …

arxiv autonomous autonomous driving cloud mapping semantic