activity
20172019
most citedGaussian Processes Semantic Map Representation

10 citations · 15 across the 2 of their papers we have counts for

collaborators
Showing cs.ROShow all

5 papers · 1 filter

cs.RO2019

Bayesian Spatial Kernel Smoothing for Scalable Dense Semantic Mapping

Lu Gan, Ray Zhang, Jessy W. Grizzle +2

This paper develops a Bayesian continuous 3D semantic occupancy map from noisy point clouds by generalizing the Bayesian kernel inference model for building occupancy maps, a binar…

cs.RO2019

LiDARTag: A Real-Time Fiducial Tag System for Point Clouds

Jiunn-Kai Huang, Shoutian Wang, Maani Ghaffari +1

Image-based fiducial markers are useful in problems such as object tracking in cluttered or textureless environments, camera (and multi-sensor) calibration tasks, and vision-based…

cs.RO2018

Hybrid Contact Preintegration for Visual-Inertial-Contact State Estimation Using Factor Graphs

Ross Hartley, Maani Ghaffari Jadidi, Lu Gan +3

The factor graph framework is a convenient modeling technique for robotic state estimation where states are represented as nodes, and measurements are modeled as factors. When desi…

cs.RO20175 cited

Sparse Bayesian Inference for Dense Semantic Mapping

Lu Gan, Maani Ghaffari Jadidi, Steven A. Parkison +1

Despite impressive advances in simultaneous localization and mapping, dense robotic mapping remains challenging due to its inherent nature of being a high-dimensional inference pro…

cs.RO201710 cited

Gaussian Processes Semantic Map Representation

Maani Ghaffari Jadidi, Lu Gan, Steven A. Parkison +2

In this paper, we develop a high-dimensional map building technique that incorporates raw pixelated semantic measurements into the map representation. The proposed technique uses G…