Deep Bayesian Future Fusion for Self-Supervised, High-Resolution, Off-Road Mapping

arXiv:2403.11876v1 Announce Type: cross
Abstract: The limited sensing resolution of resource-constrained off-road vehicles poses significant challenges towards reliable off-road autonomy. To overcome this limitation, we propose a general framework based on fusing the future information (i.e. future fusion) for self-supervision. Recent approaches exploit this future information alongside the hand-crafted heuristics to directly supervise the targeted downstream tasks (e.g. traversability estimation). However, in this paper, we opt for a more general line of development - time-efficient completion of the highest resolution …

abstract arxiv autonomy bayesian challenges cs.cv cs.lg cs.ro exploit framework fusion future general heuristics information mapping sensing supervision type vehicles