A motion-uncertainty-aware next-best-view planner for reconstructing unknown rigid objects undergoing planar motion, using Gaussian Process smoothing on noisy position measurements to evaluate expected coverage over plausible future states.
Method for registration of 3-d shapes,
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
fields
cs.RO 3years
2026 3verdicts
UNVERDICTED 3representative citing papers
A sonar-GPS fusion system using FMT local alignment and EKF global optimization reduces mapping drift by 9.5% versus baseline and achieves sub-meter accuracy in oyster farm field trials.
CooperDrive augments autonomous vehicle perception by sharing object-level data from BEV features, enabling earlier conflict anticipation and safer planning with 90 kbps bandwidth and 89 ms latency in real-world NLOS tests.
citing papers explorer
-
Motion-Uncertainty-Aware Next-Best-View Planning for Moving Object Reconstruction
A motion-uncertainty-aware next-best-view planner for reconstructing unknown rigid objects undergoing planar motion, using Gaussian Process smoothing on noisy position measurements to evaluate expected coverage over plausible future states.
-
Sonar-GPS Fusion for Seabed Mapping in Turbid Shallow Waters with an Autonomous Surface Vehicle
A sonar-GPS fusion system using FMT local alignment and EKF global optimization reduces mapping drift by 9.5% versus baseline and achieves sub-meter accuracy in oyster farm field trials.
-
CooperDrive: Enhancing Driving Decisions Through Cooperative Perception
CooperDrive augments autonomous vehicle perception by sharing object-level data from BEV features, enabling earlier conflict anticipation and safer planning with 90 kbps bandwidth and 89 ms latency in real-world NLOS tests.