We are pleased to share the code repository associated with our paper, “Probabilistic Graph-based Real-Time Ground Segmentation for Urban Robotics.” This paper has been accepted for publication in the IEEE Transactions on Intelligent Vehicles. You can access the Early Access Version of the paper here: https://ieeexplore.ieee.org/document/10487036
Currently, our team is diligently working on cleaning and documenting the repository. In just a few days, it will be fully prepared and ready for exploration!
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This package implements a ROS node for ground / obstacle / overhanging obstacle segmentation. It provides the interface to the library kf_based_terrain_analysis, which angularly exploring a poincloud from the origin to the limits, generates a graph of ground references containing their 2D coordinates (XY) and three Gaussian variables (Z, slope in X (tan(pitch)) and slope in Y (tan(roll))) with means and variances. These three variables are estimated by means of a Kalman Filter.
This package implements a ROS node for ground / obstacle / overhanging obstacle segmentation. It provides the interface to the library kf_based_terrain_analysis, which angularly exploring a poincloud from the origin to the limits, generates a graph of ground references containing their 2D coordinates (XY) and three Gaussian variables (Z, slope in X (tan(pitch)) and slope in Y (tan(roll))) with means and variances. These three variables are estimated by means of a Kalman Filter.
