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Found 9 papers, 4 papers with code
Uncertainty-Aware DNN for Multi-Modal Camera Localization
In the literature, uncertainty estimation in Deep Neural Networks (DNNs) is often performed through sampling methods, such as Monte Carlo Dropout (MCD) and Deep Ensemble (DE), at the expense of undesirable execution time or an increase in hardware resources.
Model Guided Road Intersection Classification
Understanding complex scenarios from in-vehicle cameras is essential for safely operating autonomous driving systems in densely populated areas.
WiFiNet: WiFi-based indoor localisation using CNNs
Different technologies have been proposed to provide indoor localisation: magnetic field, bluetooth , WiFi, etc.
A Benchmark for Point Clouds Registration Algorithms
In this way, we are able to cover many kinds of environment and many kinds of sensor that can produce point clouds.
Vehicle Ego-Lane Estimation with Sensor Failure Modeling
We present a probabilistic ego-lane estimation algorithm for highway-like scenarios that is designed to increase the accuracy of the ego-lane estimate, which can be obtained relying only on a noisy line detector and tracker.
Global visual localization in LiDAR-maps through shared 2D-3D embedding space
In this work we leverage Deep Neural Network (DNN) approaches to create a shared embedding space between images and LiDAR-maps, allowing for image to 3D-LiDAR place recognition.
CMRNet: Camera to LiDAR-Map Registration
In this paper we present CMRNet, a realtime approach based on a Convolutional Neural Network to localize an RGB image of a scene in a map built from LiDAR data.
A tutorial on Particle Swarm Optimization Clustering
This paper proposes a tutorial on the Data Clustering technique using the Particle Swarm Optimization approach.
ira_laser_tools: a ROS LaserScan manipulation toolbox
Under the Robot Operating System (ROS) the information generated by laser scanners can be conveyed by either LaserScan messages or in the form of PointClouds.
Robotics
