半结构化垃圾箱拣选过程的 MATLAB 代码.zip

# Semi-Structured Bin-Picking Process ## Overview This repository contains code and resources for a semi-structured bin-picking process utilizing Robotics System Toolbox and related toolboxes in MATLAB. The process is divided into three major stages: perception, motion planning, and integration. ## Requirements - MATLAB with the following toolboxes: - Robotics System Toolbox - Computer Vision Toolbox - Deep Learning Toolbox - Image Processing Toolbox - ROS Toolbox - Optimization Toolbox - Statistics and Machine Learning Toolbox - MATLAB Coder - Robotics System Toolbox Support Package for Universal Robots UR Series Manipulators - Computer Vision Toolbox Model for YOLO v4 Object Detection Support Package ## Setup 1. Install MATLAB and the required toolboxes. 2. Install the Robotics System Toolbox Support Package for Universal Robots UR Series Manipulators. 3. Install the Computer Vision Toolbox Model for YOLO v4 Object Detection Support Package. ## Usage 1. **Perception** - Use computer vision and deep learning techniques to perceive and identify objects in the bin. - Utilize the YOLO v4 object detection model from the Computer Vision Toolbox for object recognition. - Preprocess point clouds and perform PCA using functions like `findObjectPoses` for object pose estimation. 2. **Motion Planning** - Implement motion planning algorithms using Robotics System Toolbox for bin picking. - Utilize the manipulatorRRT algorithm for generating approach, pick, and place trajectories. - Incorporate trajectory optimization considering acceleration and velocity limits using Optimization Toolbox. 3. **Integration** - Integrate perception and motion planning modules for a seamless bin-picking process. - Use ROS Toolbox for communication between modules and external systems. - Generate MEX functions using MATLAB Coder for optimized performance. ## License This project is licensed under the MIT License.