WildFusion: Multimodal Implicit 3D Reconstructions in the Wild

Abstract-- We propose WildFusion, a novel approach for 3D scene reconstruction in unstructured, in-the-wild environments using multimodal implicit neural representations. This multimodal fusion generates comprehensive, continuous environmental representations, including pixel-level geometry, color, semantics, and traversability. Through real-world experiments on legged robot navigation in challenging forest environments, WildFusion demonstrates improved route selection by accurately predicting traversability. Our results highlight its potential to advance robotic navigation and 3D mapping in complex outdoor terrains. Robots need effective environmental representations to navigate safely and accomplish tasks successfully in unstructured Figure 1: WildFusion integrates LiDAR, camera, microphones, outdoor environments - often referred to as "in-thewild" and tactile sensors with implicit neural representations for settings such as monitoring high-voltage power lines continuous 3D scene reconstruction.