PRISM: Multimodal Terrain Mapping for Rover Navigation in Unstructured Environments
Robotic navigation in unstructured environments requires robust situational awareness to safely traverse hazards such as steep slopes and rocky terrain. To address this challenge, perception systems increasingly rely on multimodal sensor fusion. Specifically, integrating thermal imagery with standard optical and depth sensors enhances terrain differentiation, directly improving the reliability of mapping algorithms. This paper presents PRISM, a multimodal perception system for terrain mapping in unstructured settings. PRISM leverages a custom sensor suite to capture aligned RGB, depth, and thermal (RGB-D-T) imagery. At its core is OmniUnet, a novel vision transformer-based network specifi...
| Authors | Raul Castilla-Arquillo, Carlos Perez-del-Pulgar, Levin Gerdes et al. |
|---|---|
| Primary category | cs.RO |
| Published | 17 July 2026 |
| Last updated at source | 17 July 2026 |
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