매니퓰레이터 모션 계획

RRT와 강체 트리를 사용한 경로 계획

매니퓰레이터 모션 계획은 로봇의 자유도(DOF)와 로봇 모델의 기구학 제약 조건을 기반으로 고차원 공간에서 경로를 계획하는 작업입니다. 로봇 모델에 대한 기구학 제약 조건은 rigidBodyTree 객체로 지정됩니다. manipulatorRRT 객체를 사용하여 RRT(Rapidly-exploring Random Tree) 알고리즘에 기반하여 조인트 공간에서 경로를 계획합니다.

객체

`chompCollisionOptions`	Collision options for CHOMP trajectories (R2023a 이후)
`chompSmoothnessOptions`	Smoothness options for CHOMP trajectories (R2023a 이후)
`chompSolverOptions`	Solver options for CHOMP motion planner (R2023a 이후)
`manipulatorCHOMP`	Covariant Hamiltonian optimizer for rigid body tree motion planning (R2023a 이후)
`manipulatorRRT`	Plan motion for rigid body tree using bidirectional RRT (R2020b 이후)
`manipulatorStateSpace`	State space for rigid body tree robot models (R2021b 이후)
`manipulatorCollisionBodyValidator`	Validate states for collision bodies of rigid body tree (R2021b 이후)
`workspaceGoalRegion`	Define workspace region of end-effector goal poses (R2021a 이후)

함수

모두 확장

RRT

`plan`	Plan path using RRT for manipulators (R2020b 이후)
`interpolate`	Interpolate states along path from RRT (R2020b 이후)
`shorten`	Trim edges to shorten path from RRT (R2020b 이후)

상태공간과 유효성 검사기

`isStateValid`	Check if state is valid (R2021b 이후)
`isMotionValid`	Check if path between states is valid (R2021b 이후)

작업 공간과 유효성 검사기

`sample`	Sample end-effector poses in world frame (R2021a 이후)
`show`	Visualize workspace bounds, reference frame, and offset frame (R2021a 이후)

도움말 항목

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.

추천 예제

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. The planner explores in the joint-configuration space and searches for a collision-free path between different robot configurations. This example shows how to use the manipulatorRRT object to tune the planner parameters and plan a path between two joint configurations based on a rigidBodyTree robot model of the Franka Emika™ Panda robot. After tuning the planner parameters, the robot manipulator plans a path to move a can from one place to another.

라이브 스크립트 열기

Pick-And-Place Workflow Using CHOMP for Manipulators

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

라이브 스크립트 열기

Pick-and-Place Workflow Using RRT Planner and Stateflow for MATLAB

Setup an end-to-end pick-and-place workflow for a robotic manipulator like the KINOVA® Gen3.

라이브 스크립트 열기

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.

라이브 스크립트 열기

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.

라이브 스크립트 열기