SOURCE-LINKED INTELLIGENCE
Pose-aware Legged Robot Semantic Exploration with Omnidirectional Perception in Confined Unknown Environments
Semantic exploration in confined environments requires both environment mapping and detailed observation of target objects. For ground robots, limited sensor vertical fields of view and restricted standoff distances can leave upper object surfaces unobserved from planar viewpoints. Body tilting can improve coverage, but additional observations and posture transitions increase mission time. To address this trade-off, we present POSE, a pose-aware semantic exploration system that exploits a legged robot's intrinsic body pitch and roll with omnidirectional camera-LiDAR perception. The proposed po
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-16T22:04:07.000Z
First collected: 2026-09-19T20:28:26.698Z. This is not the publication date.