atsushisakai/pythonrobotics

PythonRobotics is a collection of Python code samples and a companion textbook covering algorithms used in robotics. The problem it solves is making robotics algorithms approachable: instead of wading through dense academic papers, a learner or researcher can run each algorithm directly and see animated visualizations of how it behaves. The project organizes algorithms into several categories. Localization algorithms help a robot figure out where it is in space, for example, Extended Kalman Filter, Particle Filter, and Histogram Filter each take sensor measurements and produce an estimated position. Mapping algorithms build a picture of the surrounding environment. SLAM (Simultaneous Localization and Mapping) combines both problems at once. Path planning algorithms, including Dijkstra, A-star, RRT, and Probabilistic Road-Map, calculate a route from one point to another while avoiding obstacles. Path tracking algorithms then steer the robot to follow that planned route. The project also covers arm navigation, aerial navigation for drones, and bipedal walking. Each example is a standalone Python script with minimal dependencies, intentionally kept simple so the underlying idea is visible in the code without library magic obscuring it. The required packages are Python 3.13, NumPy, SciPy, Matplotlib, and cvxpy. Someone would use this if they are studying robotics, autonomous vehicles, or autonomous navigation, want to experiment with a specific algorithm, or need a reference implementation to understand the mathematics before applying it in their own system.