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Manipulator Planning

Manipulator motion and path planning using RRT and CHOMP

Manipulator motion planning involves planning paths in high-dimensional space based on the degree-of-freedom (DOF) of your robot and the kinematic constraints of the robot model. Kinematic constraints for the robot model are specified as a rigidBodyTree object. Use manipulatorRRT to plan paths in the joint space using the rapidly exploring random tree (RRT) algorithm. Use manipulatorCHOMP to plan and optimize smooth, collision-free trajectories using covariant Hamiltonian optimization for motion planning (CHOMP) algorithm.

Functions

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RRT

`manipulatorRRT`	Plan motion for rigid body tree using bidirectional RRT (Since R2020b)
`plan`	Plan path using RRT for manipulators (Since R2020b)
`interpolate`	Interpolate states along path from RRT (Since R2020b)
`shorten`	Trim edges to shorten path from RRT (Since R2020b)

CHOMP

`manipulatorCHOMP`	Covariant Hamiltonian optimizer for rigid body tree motion planning (Since R2023a)
`optimize`	Optimize trajectory using CHOMP (Since R2023a)
`show`	Visualize CHOMP trajectory of rigid body tree (Since R2023a)

Sample Manipulator Configuration Space

`manipulatorStateSpace`	State space for rigid body tree robot models (Since R2021b)
`sampleUniform`	Sample state using uniform distribution (Since R2021b)
`sampleGaussian`	Sample state using Gaussian distribution (Since R2021b)

Validate Robot Configurations and Motion

`manipulatorCollisionBodyValidator`	Validate states for collision bodies of rigid body tree (Since R2021b)
`isStateValid`	Check if state is valid (Since R2021b)
`isMotionValid`	Check if path between states is valid (Since R2021b)

Define Workspace Goal Region

`workspaceGoalRegion`	Define workspace region of end-effector goal poses (Since R2021a)
`sample`	Sample end-effector poses in world frame (Since R2021a)
`show`	Visualize workspace bounds, reference frame, and offset frame (Since R2021a)

Topics

Pick and Place Using RRT for Manipulators
Using manipulators to pick and place objects in an environment may require path planning algorithms like the rapidly-exploring random tree planner.
Pick-and-Place Workflow Using RRT Planner and Stateflow for MATLAB
This example shows how to setup an end-to-end pick-and-place workflow for a robotic manipulator like the KINOVA® Gen3.
Pick-and-Place Workflow in Gazebo Using Point-Cloud Processing and RRT Path Planning
Set up an end-to-end, pick-and-place workflow for a robotic manipulator like the KINOVA® Gen3.
Plan Paths With End-Effector Constraints Using State Spaces For Manipulators
Plan a manipulator robot path using sampling-based planners like the rapidly-exploring random trees (RRT) algorithm.

Featured Examples

Detect and Harvest Fruit Using UR10 Manipulator in Gazebo

Setup UR10 manipulator and simulate environment in Gazebo simulator to perform fruit pick-and-place application.

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Plan Path for Manipulator in Simulink with Robotics System Toolbox™

Execute and simulate a basic path planning task in Simulink®. This example uses code generation to illustrate a pattern for executing autonomy functions from MATLAB® in Simulink.

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Pick-And-Place Workflow Using CHOMP for Manipulators

Use CHOMP to plan smooth and collision-free trajectories for a pick-and-place workflow

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Motion Planning for Backhoe Using RRT

Plan a path for a backhoe, in an environment that contains obstacles, by using a motion planner. In this example, you model the backhoe in simplified form as a kinematic tree, then use a sampling-based motion planner to determine a viable path for the backhoe between two poses in the presence of obstacles. Simulate the outcome in a Simscape™ Multibody™ model.

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