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RRT および剛体ツリーを使用したパス計画

マニピュレーター動作の計画には、ロボットの自由度 (DOF) およびロボット モデルの運動学的拘束に基づいた高次元の空間でのパスの計画が含まれます。ロボット モデルの運動学的拘束は、rigidBodyTree オブジェクトとして指定されます。manipulatorRRT を使用して、Rapidly-Exploring Random Tree (RRT) アルゴリズムを使用したジョイント空間でパスを計画します。


manipulatorRRTPlan motion for rigid body tree using bidirectional RRT
planPlan path using RRT for manipulators
interpolateInterpolate states along path from RRT
shortenTrim edges to shorten path from RRT
workspaceGoalRegionDefine workspace region of end-effector goal poses
sampleSample end-effector poses in world frame
showVisualize workspace bounds, reference frame, and offset frame


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.

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

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