Motion Planning

Path metrics, RRT path planners, path following

Use motion planning to plan a path through an environment. You can use common sampling-based planners like RRT, RRT*, and Hybrid A*, or specify your own customizable path-planning interfaces. Use path metrics and state validation to ensure your path is valid and has proper obstacle clearance or smoothness. Follow your path and avoid obstacles using pure pursuit and vector field histogram algorithms.

Functions

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Paths and Path Segments

`navPath`	Planned path
`dubinsConnection`	Dubins path connection type
`dubinsPathSegment`	Dubins path segment connecting two poses
`reedsSheppConnection`	Reeds-Shepp path connection type
`reedsSheppPathSegment`	Reeds-Shepp path segment connecting two poses

Path Metrics

`pathmetrics`	Information for path metrics
`clearance`	Minimum clearance of path
`isPathValid`	Determine if planned path is obstacle free
`smoothness`	Smoothness of path
`show`	Visualize path metrics in map environment

State Spaces

`stateSpaceSE2`	SE(2) state space
`stateSpaceSE3`	SE(3) state space
`stateSpaceDubins`	State space for Dubins vehicles
`stateSpaceReedsShepp`	State space for Reeds-Shepp vehicles

State Validation

`validatorOccupancyMap`	State validator based on 2-D grid map
`validatorOccupancyMap3D`	State validator based on 3-D grid map
`validatorVehicleCostmap`	State validator based on 2-D costmap
`isStateValid`	Check if state is valid
`isMotionValid`	Check if path between states is valid

Motion Planning

`plannerRRT`	Create an RRT planner for geometric planning
`plannerRRTStar`	Create an optimal RRT path planner (RRT*)
`plannerBiRRT`	Create bidirectional RRT planner for geometric planning
`plannerAStarGrid`	A* path planner for grid map
`plannerHybridAStar`	Hybrid A* path planner

Frenet Trajectory Generation

`referencePathFrenet`	Smooth reference path fit to waypoints
`trajectoryGeneratorFrenet`	Find optimal trajectory along reference path
`trajectoryOptimalFrenet`	Find optimal trajectory along reference path

Custom Path Planning Interfaces

`createPlanningTemplate`	Create sample implementation for path planning interface
`nav.StateSpace`	Create state space for path planning
`nav.StateValidator`	Create state validator for path planning

Path Following

`controllerVFH`	Avoid obstacles using vector field histogram
`controllerPurePursuit`	Create controller to follow set of waypoints

Dynamic Capsule List

`dynamicCapsuleList`	Dynamic capsule-based obstacle list
`dynamicCapsuleList3D`	Dynamic capsule-based obstacle list
`addEgo`	Add ego bodies to capsule list
`addObstacle`	Add obstacles to 2-D capsule list
`checkCollision`	Check for collisions between ego bodies and obstacles
`egoGeometry`	Geometric properties of ego bodies
`egoPose`	Poses of ego bodies
`obstacleGeometry`	Geometric properties of obstacles
`obstaclePose`	Poses of obstacles

Blocks

Pure Pursuit	Linear and angular velocity control commands
Vector Field Histogram	Avoid obstacles using vector field histogram

Topics

Choose Path Planning Algorithms for Navigation

Details about the benefits of different path and motion planning algorithms.

Plan Mobile Robot Paths Using RRT

This example shows how to use the rapidly-exploring random tree (RRT) algorithm to plan a path for a vehicle through a known map.

Moving Furniture in a Cluttered Room with RRT

This example shows how to plan a path to move bulky furniture in a tight space avoiding poles.

Motion Planning with RRT for a Robot Manipulator

Plan a grasping motion for a Kinova Jaco Assistive Robotics Arm using the rapidly-exploring random tree (RRT) algorithm.

Dynamic Replanning on an Indoor Map

This example shows how to perform dynamic replanning on a warehouse map with a range finder and an A* path planner.

Highway Lane Change

This example shows how to simulate an automated lane change maneuver system for highway driving scenario.

Highway Trajectory Planning Using Frenet Reference Path

This example demonstrates how to plan a local trajectory in a highway driving scenario.

Optimal Trajectory Generation for Urban Driving

This example shows how to perform dynamic replanning in an urban scenario using trajectoryOptimalFrenet.

Motion Planning in Urban Environments Using Dynamic Occupancy Grid Map

This example shows you how to perform dynamic replanning in an urban driving scene using a Frenet reference path.

Path Following with Obstacle Avoidance in Simulink®

This example shows you how to use Simulink to avoid obstacles while following a path for a differential drive robot.

Obstacle Avoidance with TurtleBot and VFH

This example shows how to use ROS Toolbox and a TurtleBot® with vector field histograms (VFH) to perform obstacle avoidance when driving a robot in an environment.

Vector Field Histogram

VFH algorithm details and tunable properties.

Pure Pursuit Controller

Pure Pursuit Controller functionality and algorithm details.

Featured Examples

Plan Mobile Robot Paths Using RRT

Use the rapidly-exploring random tree (RRT) algorithm to plan a path for a vehicle through a known map. Special vehicle constraints are also applied with a custom state space. You can tune your own planner with custom state space and path validation objects for any navigation application.

Open Live Script

Dynamic Replanning on an Indoor Map

Perform dynamic replanning on a warehouse map with a range finder and an A* path planner.

Open Live Script

Highway Lane Change

Simulate an automated lane change maneuver system for highway driving scenario.

Open Script

Highway Trajectory Planning Using Frenet Reference Path

Demonstrates how to plan a local trajectory in a highway driving scenario. This example uses a reference path and dynamic list of obstacles to generate alternative trajectories for an ego vehicle. The ego vehicle navigates through traffic defined in a provided driving scenario from a drivingScenario object. The vehicle alternates between adaptive cruise control, lane changing, and vehicle following maneuvers based on cost, feasibility, and collision-free motion.

Open Live Script