74 citations · 237 across the 8 of their papers we have counts for
9 papers
Energy-based Legged Robots Terrain Traversability Modeling via Deep Inverse Reinforcement Learning
Lu Gan, Jessy W. Grizzle, Ryan M. Eustice +1
This work reports on developing a deep inverse reinforcement learning method for legged robots terrain traversability modeling that incorporates both exteroceptive and propriocepti…
Dynamic Semantic Occupancy Mapping using 3D Scene Flow and Closed-Form Bayesian Inference
Aishwarya Unnikrishnan, Joey Wilson, Lu Gan +4
This paper reports on a dynamic semantic mapping framework that incorporates 3D scene flow measurements into a closed-form Bayesian inference model. Existence of dynamic objects in…
Multitask Learning for Scalable and Dense Multilayer Bayesian Map Inference
Lu Gan, Youngji Kim, Jessy W. Grizzle +4
This article presents a novel and flexible multitask multilayer Bayesian mapping framework with readily extendable attribute layers. The proposed framework goes beyond modern metri…
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…
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…
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…