로봇 매니퓰레이터

ROS 또는 ROS 2 네트워크를 통해 로봇 매니퓰레이터 애플리케이션을 설계하고 배포

ROS Toolbox를 사용하면 Gazebo 또는 Unity^®와 같은 ROS 지원 시뮬레이터에 연결하여 시뮬레이션 환경에서 Kinova^® Robot Arm 또는 Universal Robots UR 시리즈 매니퓰레이터 같은 로봇 매니퓰레이터 모델을 사용해 애플리케이션을 시뮬레이션할 수 있습니다.

Robotics System Toolbox™를 사용해 로봇 매니퓰레이터를 모델링하여 충돌 회피를 위한 작업-공간의 이해와 모션 계획을 시연할 수 있습니다. 그런 다음 ROS Toolbox를 통해 시뮬레이터와 통신 채널을 설정하고 엔드 투 엔드 픽앤플레이스 워크플로와 같은 애플리케이션을 시뮬레이션할 수 있으며, ROS Toolbox를 사용해 ROS 메시지를 통해 제어 명령을 전송하여 로봇 매니퓰레이터를 조종하고 Gazebo 또는 Unity에서 시뮬레이션된 궤적을 볼 수 있습니다.

추천 예제

Pick-and-Place Workflow in Gazebo Using ROS

Setup an end-to-end pick-and-place workflow for a robotic manipulator like the Kinova® Gen3 and simulate the robot in the Gazebo physics simulator.

Pick-and-Place Workflow in Unity 3D Using ROS

Set up an end-to-end pick-and-place workflow for a robotic manipulator like the Kinova Gen3, and simulate the robot in the Unity game engine.

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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.

Control PR2 Arm Movements Using ROS Actions and Inverse Kinematics

Send commands to robotic manipulators in MATLAB®. Joint position commands are sent via a ROS action client over a ROS network. This example also shows how to calculate joint positions for a desired end-effector position. A rigid body tree defines the robot geometry and joint constraints, which is used with inverse kinematics to get the robot joint positions. You can then send these joint positions as a trajectory to command the robot to move.

Design and Simulate Warehouse Pick-and-Place Application Using Mobile Manipulator in Simulink and Gazebo

Set up an end-to-end, pick-and-place workflow for a mobile manipulator using Simulink® and Gazebo®.

Generate Automated ros_control Plugin for 3-D Shape Tracing Manipulator

Generate and deploy a 3-D shape tracing contoller as a ros_control plugin from Simulink. Perform 3-D shape tracing using UR manipulator and depth point cloud.

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Design and Validate Object Detection and Motion Planning Algorithms Using Gazebo, OpenCV, and MATLAB

Design and validate complex application workflows for a robotic manipulator like the Kinova Gen3 7-DoF Ultralightweight Robot using Gazebo® physics simulator, OpenCV, Robotics Systems Toolbox™ and ROS Toolbox.

Getting Started with Connecting and Controlling a UR5e Cobot from Universal Robots

Use the urROSNode object to connect with a Universal Robots cobot and move the robot using joint space control, task space control, waypoint tracking in task space, and waypoint tracking in joint space. This example uses Robotics Systems Toolbox™ and ROS Toolbox.

Getting Started with Standalone ROS Node Generation for Universal Robots

Plan, create and validate a deployable motion planning standalone ROS node for Universal Robot UR5e with URSim, Gazebo simulator or physical UR5e. In this example, you will

Semi-Structured Intelligent Bin Picking for UR5e Using YOLO and PCA-Based Object Detection

Detailed workflow for intelligent bin picking using Universal Robots UR5e cobot. The MATLAB project provided with this example consists of the Initialize, Perception, Motion Planning, and Integration modules (project folders) to create a complete bin picking workflow.