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Navigation Toolbox

Design, simulate, and deploy algorithms for autonomous navigation

Navigation Toolbox™ provides algorithms and analysis tools for motion planning, simultaneous localization and mapping (SLAM), and inertial navigation. The toolbox includes customizable search and sampling-based path-planners, as well as metrics for validating and comparing paths. You can create 2D and 3D map representations, generate maps using SLAM algorithms, and interactively visualize and debug map generation with the SLAM map builder app. The toolbox provides sensor models and algorithms for localization. You can simulate and visualize IMU, GPS, and wheel encoder sensor data, and tune fusion filters for multi-sensor pose estimation.

Reference examples are provided for automated driving, robotics, and consumer electronics applications. You can test your navigation algorithms by deploying them directly to hardware (with MATLAB® Coder™ or Simulink® Coder).

Get Started

Learn the basics of Navigation Toolbox

Sensor Models

Calibration and simulation for IMU, GPS, and range sensors

Localization and Pose Estimation

Inertial navigation, pose estimation, scan matching, Monte Carlo localization

Mapping

2-D and 3-D occupancy maps, egocentric maps, raycasting

SLAM

2-D and 3-D simultaneous localization and mapping

Motion Planning

Path metrics, RRT path planners, path following

Coordinate Transformations and Trajectories

Quaternions, rotation matrices, transformations, trajectory generation