d-star-lite

Motion planning(Path Planning and Trajectory Planning/Tracking) of AGV/AMR：python implementation of Dijkstra, A*, JPS, D*, LPA*, D* Lite, (Lazy)Theta*, RRT, RRT*, RRT-Connect, Informed RRT*, Voronoi, PID, DWA, APF, LQR, MPC, RPP, Bezier, Dubins etc.

This repository contains path planning algorithms in C++ for a grid based search.

Autonomous UAV navigation in GNSS-denied indoor spaces with no prior map: stereo VIO (MSCKF) and lidar-inertial odometry with map-based relocalization (SLAM), 3D occupancy mapping, D* Lite path planning and GPU MPPI obstacle avoidance. PX4 + ROS 2 + Gazebo SITL, DARPA SubT Urban.

This is a C++ repository containing various algorithms implemented by me for solving robotics problems

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.

Python D* Lite implementation

Interactive path planning with D*Lite on Raspberry Pi for Lego EV3 robots

This project implements the dijkstra, A* and D* Lite algorithms and compares them.

Implementation of d-star-lite and a-star algorithms

Grid-based path planning for a differential drive robot

Algernon is a JS library for efficiently generating, solving, and rendering mazes.

Certified route planning under drifting costs: conformal certificates (LB<=OPT<=UB), certificate-directed sensing, proof-gated ns-us preprocessing, and an observable-coverage layer (WATCH + Shiryaev-Roberts). 250 tests, validated on real METR-LA.

Simple and safe real-time navigation for no-noise differential-drive agent with LIDAR for escaping static environments.

Visualizes search algorithms, including A*, LPA*, and D* Lite.

Single-Agent Pathfinding Visualizer

A real-time AI pathfinding visualizer featuring D* Lite, A*, and Greedy algorithms with dynamic re-planning capabilities

Implementations of reactive navigation and map-based navigation algorithms such as RRT, D* Lite, Bug2, and Bug Tangent. The Turtlebot3 Waffle model was used for testing, in addition to software such as CoppeliaSim for simulations.

Experiment setup for my paper about dynamic path-planning using D* Lite for Discrete Math (Semester 2 24/25).

Implementation of Incremental Path Planning (D*-Lite) in Pacman Domain

Reproducible 3D/4D UAV path-planning benchmark for dense cities, dynamic hazards, and collision-certified trajectory smoothing.