Explore and analyze LiDAR data from Global Ecosystem Dynamics Investigation (GEDI) of NASA
-
Updated
Jun 24, 2021 - R
Explore and analyze LiDAR data from Global Ecosystem Dynamics Investigation (GEDI) of NASA
Implementation of the Extended Kalman Filter in C++
Extended Kalman Filter on LiDAR and Radar sensor feed
Implemented sensor fusion algorithm using an extended Kalman filter that tracks nearby moving objects using RADAR and LIDAR measurements.
Raspberry Pi powered robot with camera live stream and 360° lidar.
Simulation of a LiDAR (Light Detection and Ranging) sensor
Containerized ROS node that communicates with x4 lidar via USB pass though from the docker host
The Light Imaging Detection and Ranging (LIDAR) is a method for measuring distances (ranging) by illuminating the target with laser light and measuring the reflection with a sensor. The LIDAR Sensor escalates the entire mechanism with great efficiency which is notified with process and main activation codes.
An Extended Kalman Filter Project
Implementation using only LASER (LIDAR) measurements to predict a pedestrian
Implementing Extended Kalman Filter in C++
Utilize an Extended Kalman Filter to estimate the state of a moving object of interest with noisy Lidar and Radar measurements
Assignments and Projects for the UNSW Advanced Autonomous Systems Term 1 2019
.net wrapper of YDLidar sdk
Utilize an Unscented Kalman Filter to estimate the state of a moving object of interest with noisy Lidar and Radar measurements
Utilized an Extended Kalman Filter and Sensor Fusion to estimate the state of a moving object of interest with noisy lidar and radar measurements. The project involved utilzing lidar data (Point Cloud) for position and radar data (Doppler) for radial velocity.
A LiDAR 3D Mapping system which is very low cost at 5000₹(~80$) made using arduino.
Slamtec RPLIDAR with a Raspberry PI
High-performance localization software for autonomous vehicles. A particle filter is combined with a map to localize a vehicle.
Add a description, image, and links to the lidar-measurements topic page so that developers can more easily learn about it.
To associate your repository with the lidar-measurements topic, visit your repo's landing page and select "manage topics."