RISS 2018 - Segmentation of sparse LIDAR point clouds
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Updated
Jul 25, 2018 - Makefile
RISS 2018 - Segmentation of sparse LIDAR point clouds
Reconstruction of Indoor Environments Using VLP-16 and Tinkerforge IMU 2.0
Our implementation of an Autonomous delivery drone system. This project was created under the aegis of E-Yantra robotics competition and uses ROS and Gazebo simulator with various environments to test.
Sensor fusion of LiDAR, camera, and radar for autonomous vehicles using C++
This repository is used for assignments for various learning modules of ROS. All assignments and projects are physically implemented on TurtleBot3 Burger.
Use lidar car data to detect incoming road obstacles track multiple cars on the road, estimating their positions and speed
Obstacle Detection using LiDAR Point Cloud, RANSAC, and Euclidean Clustering.
This repository is detined for the puzzlebot robot with a camera and a LiDAR sensor mounted. The main objective of this project is navigate through a series of points defined and estimate position based on the dynamic model and Kalman Filter correction using defined Arucos at specific positions in the world. This project was created using Melodic
Pointcloud objects detection and ground vs nonground segmentation using the PCL library.
SFND_Lidar_Obstacle_Detection
This code was used to implement a sagittal-plane LIDAR for the Scott Robot, as part of a project I worked on at Plymouth University. A custom, lightweight ROS node is used to encode LIDAR readings into a 2D image, which is then analysed using OpenCV algorithms as a proof-of-concept.
Highlights of the Project: Filtering, Segmentation, Clustering, and Bounding boxes.
Bachelor's project in computer engineering at AUT
This repository contains the senior design project for a Mechatronics Engineering undergraduate, focused on developing an autonomous mobile robot equipped with SLAM (Simultaneous Localization and Mapping) and LiDAR technology for environmental exploration and monitoring
Drone navigation and collision avoidance Gazebo
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