SLAM algorithm with ultrasound range input implemented on a Crazyflie drone
- Updated
Mar 20, 2020 - Python
SLAM algorithm with ultrasound range input implemented on a Crazyflie drone
ROS-based multi-agent system for path planning and LiDAR SLAM mapping in dynamic environments.
This project is a hands-on implementation to explore and understand the concepts behind Simultaneous Localization and Mapping (SLAM). It uses a simulated laser sensor to detect obstacles and create a map of the environment in real-time. The system continuously updates the map based on sensor data and accounts for uncertainty in the measurements.
A ROS2 Package of a Webots Simulation of 2-Wheel Differential Drive Robot Capable of SLAM and Autonomous Navigation
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