3 accepted papers
Localizing ground robots against aerial imagery provides a critical capability for autonomous navigation, especially in environments where GPS is unreliable or unavailable. This task is challenging due to large viewpoint differences and substantial environmental variability. Most prior methods local…
Aerial imagery provides essential global context for autonomous navigation, enabling route planning at scales inaccessible to onboard sensing. We address the problem of generating global costmaps for long-range planning directly from satellite imagery when entities and mission-specific traversal rul…
We study the problem of decentralized classification conducted over a network of mobile sensors. We model the multiagent classification task as a hypothesis testing problem where each sensor has to almost surely find the true hypothesis from a finite set of candidate hypotheses. Each sensor makes no…