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-lane-boundary-and-vehicle-detections

arm_planning

awesome-machine-learning-cn

机器学习资源大全中文版，包括机器学习领域的框架、库以及软件

awesome-matlab-robotics

This is a list of awesome demos, tutorials, utilities and overall resources for the robotics community that use MATLAB and Simulink.

awesome-rl

Reinforcement learning resources curated

awesome-robotics

A curated list of awesome links and software libraries that are useful for robots.

awesome-robotics-libraries

:sunglasses: A curated list of robotics libraries and software

books

【编程随想】收藏的电子书清单（多个学科，含下载链接）

d2l-zh

《动手学深度学习》：面向中文读者、能运行、可讨论。中英文版被全球175所大学采用教学。

deep-learning-interview-book

深度学习面试宝典（含数学、机器学习、深度学习、计算机视觉、自然语言处理和SLAM等方向）

deep_object_pose

Deep Object Pose Estimation (DOPE) – ROS inference (CoRL 2018)

designing-robot-manipulator-algorithms

MATLAB and Simulink files for modeling and simulation of ROBOTIS OpenManipulator

getting-started-ros

Resources for getting started with MATLAB and Simulink and the Robot Operating System (ROS).

gpd

Detect grasp poses in point clouds

ikfastpy

Python wrapper over OpenRave's IKFast inverse kinematics solver for a UR5 robot arm.

matlab-rrt-variants

RRT*, RRT-connect, lazy RRT and RRT extend have been implemented for 2d and 3d c-spaces with visualization

modernroboticscpp

Modern Robotics: Mechanics, Planning, and Control C++ Library --- The primary purpose of the provided software is to be easy to read and educational, reinforcing the concepts in the book. The code is optimized neither for efficiency nor robustness. http://modernrobotics.org/

mpnet

Motion Planning Networks

paddledetection

Object detection and instance segmentation toolkit based on PaddlePaddle.

pathplanning

Common used path planning algorithms with animations.

phd-bibliography

References on Optimal Control, Reinforcement Learning and Motion Planning

posecnn

A Convolutional Neural Network for 6D Object Pose Estimation in Cluttered Scenes

practicalai-cn

AI实战-practicalAI 中文版

pythonrobotics

Python sample codes for robotics algorithms.

redundant-manipulators

robot-grasp-detection

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.

robot_motion_planning

Package for bidirectional motion planning for mobile manipulation tasks involving geometric end-effector task constraints

robotics

Simulation of Kinematic Control: Obstacles Avoidance of Redundant Manipulator

robotrrt

The RRT method with 7-arm redundant manipulators

sampling_based_tube_following

Code to reproduce research results from "Sampling-based Tube Following for Redundant Robotic Manipulators"