Книга "Архитектура сложных веб-приложений. С примерами на Laravel"

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.

[ICRA 2022] CaTGrasp: Learning Category-Level Task-Relevant Grasping in Clutter from Simulation

Deep learning for grasp detection within MoveIt.

An implementation of our RA-L work 'Real-world Multi-object, Multi-grasp Detection'

Toolbox for our GraspNet-1Billion dataset.

GRAB: A Dataset of Whole-Body Human Grasping of Objects

A curated list of awesome grasping libraries and resources

Robotic grasp dataset for multi-object multi-grasp evaluation with RGB-D data. This dataset is annotated using the same protocal as Cornell Dataset, and can be used as multi-object extension of Cornell Dataset.

Tutorial on DDD (Domain-Driven Design), by building a Web App with the theme "Personal Finance Management". Adapted from a group project in university.

RCM is a simple CRM application designed for Auto Parts Store made with ASP.NET Core based on DDD, CQRS and SOLID Principles.

paper list of robotic grasping and some related works

This is my implementation of a branch and price algorithm to solve the humanitarian aid distribution problem. This problem is a VRP with a specific objective function

A grasp simulation environment in gazebo: UR robot arm with a 85mm robotiq gripper that can be drived to grasp things through moveit

cornell grasp dataset analyses and process

[ICLR 2022] The Unreasonable Effectiveness of Random Pruning: Return of the Most Naive Baseline for Sparse Training by Shiwei Liu, Tianlong Chen, Xiaohan Chen, Li Shen, Decebal Constantin Mocanu, Zhangyang Wang, Mykola Pechenizkiy

a simple Matlab gui for annotating rotated grasping bounding box

This repository was created for the subject of Computer Theory. The propose of this subject is to improve your skills to solve the 0-1 knapsack problem of different ways. The techniques used were Dynamic Programing and two metaheuristics (which are GRASP and TABU search).

Run our ROS noetic environment including the workspace and projects

This Repository is for simulating a simple grasping behaviour using visual feedback