FASTC: A Fast Attentional Framework for Semantic Traversability Classification Using Point Cloud

arXiv:2406.16564v1 Announce Type: new
Abstract: Producing traversability maps and understanding the surroundings are crucial prerequisites for autonomous navigation. In this paper, we address the problem of traversability assessment using point clouds. We propose a novel pillar feature extraction module that utilizes PointNet to capture features from point clouds organized in vertical volume and a 2D encoder-decoder structure to conduct traversability classification instead of the widely used 3D convolutions. This results in less computational cost while even better performance is achieved …

abstract arxiv assessment autonomous classification cloud cs.cv extraction feature feature extraction features framework maps navigation novel paper problem semantic type understanding