A fully visualized implementation of the Dynamic Window Approach (DWA) in Python using Pygame. Simulate and visualize obstacle avoidance and goal-reaching for mobile robots in 2D space — perfect for robotics beginners, path planning researchers, and AI robotics students!
A modular SLAM system combining Particle Filter-based localization, Occupancy Grid Mapping (OGM), Dynamic Window Approach (DWA) for real-time obstacle avoidance, and D* Lite for global path replanning. This project integrates both probabilistic mapping and real-time motion planning, suitable for research and educational use in robotics.
ROS Noetic-based navigation stack for the Pickasso Robot, featuring AMCL localization, DWA path planning, and obstacle avoidance in both Gazebo simulation and real-world TurtleBot3 Waffle Pi deployments
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