iris2333 Goto Github PK
Type: User
Type: User
A ROS package to detect grasp poses in point clouds.
A ROS wrapper of the AprilTags 2 visual fiducial detector
MIT-Princeton Vision Toolbox for Robotic Pick-and-Place at the Amazon Robotics Challenge 2017 - Grasp Detection and Image Matching for Novel Objects with Deep Learning
Code from Robot Learning Lab, Cornell in paper Deep Learning for Detecting Robotic Grasps
Simple, straighforward ROS library for hand-eye calibration
Mask RCNN in TensorFlow
Fully Convolutional Instance-aware Semantic Segmentation
Generative Grasping CNN from "Closing the Loop for Robotic Grasping: A Real-time, Generative Grasp Synthesis Approach" (RSS 2018)
Detect grasp poses in point clouds
Code and documentation for the winning sollution to the Grasp-and-Lift EEG Detection challenge
Code to detect planar grasps
Tools for using the Kinect One (Kinect v2) in ROS
Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow
This repository contains exercise files of the book "Mastering ROS for Robotics Programming"
Models and examples built with TensorFlow
Generate basic grasp poses for simple objects such as blocks or cylinders
机器人视觉 移动机器人 VS-SLAM ORB-SLAM2 深度学习目标检测 yolov3 行为检测 opencv PCL 机器学习 无人驾驶
Detecting robot grasping positions with deep neural networks. The model is trained on Cornell Grasping Dataset. This is an implementation mainly based on the paper 'Real-Time Grasp Detection Using Convolutional Neural Networks' from Redmon and Angelova.
Implementation of YOLO v3 object detector in Tensorflow (TF-Slim)
Universal Robot (UR3) Pick and Place Hardware Implementation with ROS using a USB Cam and an Electromagnetic Gripper
The goal of the project is to implement robotic agents that could rapidly build structures from random objects in a disaster/crisis situation to facilitate operation of other robotic agents, or fast and affordable accommodation of the injured groups, e.g. to facilitate operation of rescue agents in a post-earthquake situation. We are proposing a system that employs robotics manipulators (UR5 industrial arm equipped with a gripper in our experiments) to stack objects with arbitrary shapes to construct a rigid wall. Some of the challenges in this problem are: 1) Planning the optimal stacking order and relative placing of the objects 2) Reliable grasping and transporting of arbitrarily shaped objects 3) Accurate detection and localization of the arm and the objects The system is being implemented over ROS to connect to and control the UR5 arm, and MoveIt package is employed to perform collision aware trajectory planning for the manipulator/grasper set. A variety of objects with different shapes and features, e.g. deformability, are considered for the experiments.
Train robotic agents to learn to plan pushing and grasping actions for manipulation with deep reinforcement learning.
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.