tezchan Goto Github PK

16811_project

Path planning for multiple constrained robots.

a-passivity-based-regressor-free-adaptive-controller-for-robot-manipulators-with-combined-regressor-

anti-windup-compensator

List of additional files available for the interested reader of "Vibration Control Subjected to Windup Problem: An Applied View on Analysis and Synthesis with Convex Formulation"

awsl

Auto AWSLing

bilateral-teleoperation-system

china-holiday-calender

**节假日、调休、补班日历，ICS格式，可供IPhone、Google Calender、Outlook等客户端订阅

cooperative-localization-using-pi

Matlab implementation of a cooperative localization for multiple robots, localizing in a global map.

cpprobotics

cpp implementation of robotics algorithms including localization, mapping, SLAM, path planning and control

deep-reinforcement-learning-arm-manipulation-project-using-dqn-agent

Robotics-Deep Reinforcement Learning Project: Deep RL Arm Manipulation by using DQN (Deep Q-Learning Network) agent simulated on ROS-Gazebo with C++ API.

drake

Model-based design and verification for robotics.

dual-arm-robot-force-controlled-object-manipulation

This Repository is the complete workspace of a project that realizes force-controlled object manipulation with a dual-arm-robot (UR5 and UR10)

eec-693-robot-modeling-and-control

Cleveland State University - EEC 693 Robot Modeling and Control - Hanz Richter - Spring 2019

enpm661-planning-for-autonomous-robots

Planning is a fundamental capability needed to realize autonomous robots. Planning in the context of autonomous robots is carried out at multiple different levels. At the top level, task planning is performed to identify and sequence the tasks needed to meet mission requirements. At the next level, planning is performed to determine a sequence of motion goals that satisfy individual task goals and constraints. Finally, at the lowest level, trajectory planning is performed to determine actuator actions to realize the motion goals. Different algorithms are used to achieve planning at different levels. This graduate course will introduce planning techniques for realizing autonomous robots. In addition to covering traditional motion planning techniques, this course will emphasize the role of physics in the planning process. This course will also discuss how the planning component is integrated with control component. Mobile robots will be used as examples to illustrate the concepts during this course. However, techniques introduced in the course will be equally applicable to robot manipulators.

feedforward-control

forcedimensionomega7

hanting_based_on_voronoi

本仓库是对论文《Intercepting Rogue Robots: An Algorithm for Capturing Multiple Evaders With Multiple Pursuers》的matlab复现，基于voronoi图最小化围捕算法

haptic-control

Real-time controller of Force Dimension delta.3 for reaching tasks on Chai3D

human_shadow_cyton300e

Robotics-Autumn2020 Project

kst-kuka-sunrise-toolbox

A ToolBox for controlling KUKA iiwa robot from matlab:

kuka

根据kuka机器人的D-H表编写其雅克比矩阵计算MATLAB代码

kuka_experimental

Experimental packages for KUKA manipulators within ROS-Industrial (http://wiki.ros.org/kuka_experimental)

leader-follower

Formation control of multiple unicycle robots (MATLAB)

machine-learning-and-convex-optimization-in-teleoperation-system

multiple haptic rendering experiments for optimal path control and collision detection of robotics

mastering_ros

This repository contains exercise files of the book "Mastering ROS for Robotics Programming"

matlab-robotics-toolbox

Modeling and simulation by robotics toolbox

matrix_derivatives

This is a note on matrix derivatives and described my own experience in detail. Hope you'll like it.

mj_envs

A collection of MuJoCo based environments.

mobile-multi-robot-system

mobile-robot-simulation-tested-on-single-robot-

Many simulations including single robot and multi robots

mobile-robotics-control-and-simulation

The 5 basic principles of Robotics namely, Kinematics, Locomotion, Perception, Localization, and both planning and navigation have been used to operate various mobile robots in multiple Simulation Environments.