SOCC-ICP unifies semantic occupancy grid mapping with LiDAR scan alignment via adaptive point-to-point or point-to-plane ICP, achieving competitive odometry performance while producing maps usable for planning.
Method for registration of 3-d shapes
4 Pith papers cite this work. Polarity classification is still indexing.
4
Pith papers citing it
fields
cs.RO 4years
2026 4verdicts
UNVERDICTED 4representative citing papers
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.
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
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SOCC-ICP: Semantics-Assisted Odometry based on Occupancy Grids and ICP
SOCC-ICP unifies semantic occupancy grid mapping with LiDAR scan alignment via adaptive point-to-point or point-to-plane ICP, achieving competitive odometry performance while producing maps usable for planning.
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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.
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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.
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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.