Collaborative Maze Navigation with e-puck Robots
Project Overview
This project implements a LiDAR-based autonomous exploration and navigation system in Webots. The robot incrementally builds a 2D occupancy grid from LiDAR measurements, using GPS and compass data for localization. The resulting map is used for obstacle avoidance, exploration, and autonomous path planning.
Simulation Run
Algorithm Implementation
LiDAR measurements are transformed into the global frame and used to update the occupancy grid, with Bresenham's algorithm applied to trace free space along each LiDAR ray. BFS and DFS are used for exploration and target selection, while BFS-based path planning generates collision-free routes through known free space. A PID controller regulates the robot's heading and forward motion, with replanning and stuck/dead-end detection providing recovery during navigation.
Project Documentation
SLAM Report
Mapping accuracy analysis and path planning algorithm verification.