helloxss Goto Github PK

quantitative

Optimal experimental design with automatic differentiation using the Fisher information matrix and Cramer-Rao Bound

reinforcement-learning-car

Using reinforcement learning to teach a car to avoid obstacles.

repository

大家想要什么其他的软件，可以提交Issues哦

riderid

Source code for the bicycle rider control system identification in "Rider control identification in bicycling using lateral force perturbation tests", Schwab, de Lange, Happee, Moore, 2013..

riptide_software

The software packages which power The OSU Underwater Robotics Team's AUV.

rl

The Robotics Library (RL) is a self-contained C++ library for rigid body kinematics and dynamics, motion planning, and control.

rl-rc-car

Implements basic reinforcement learning algorithms to control a remote-control car in a room.

rmc_final

Final Project for RMC Praktikum

robot-kinematic-and-dynamic-modeling

Kinematic and dynamic modeling for the Stäubli TX90 series Industrial Robots done in matlab

robot_pathplanning

IMAT3404 Mobile Robotics: Plan and follow a path from a pre-determined start point to a pre-determined end point in a given known map which you should be able to load into your program.

saclib

A C++ header-only library implementation of sequential action control (SAC)

segwaycontrols

Academic Project Segway Control System [Simulink, Matlab, Maple]

simflight

Simulation environment for flight systems

simiam

A MATLAB-based educational bridge between theory and practice in robotics.

simulator

A ROS/ROS2 Multi-robot Simulator for Autonomous Vehicles

slugs

Santa Cruz Low-Cost UAV GNC System (SLUGS) is an open source (hardware and software) UAV autopilot developed at UCSC

softcon

SoftCon: Simulation and Control of Soft-Bodied Animals with Biomimetic Actuators

solution-to-equations-of-motion-for-underwater-glider

Equations of motion towards underwater glider were formulated at Princeton by Graver in his PhD work in 2005.Various marine engineers use them to develop different guidance, navigation and control system towards efficient functioning of the glider.This code simulates the results of Graver (2005) towards solving equations of motion of underwater glider. The MATLAB code is properly commented for the input parameters to be used in simulation of glider motion. Our request is just to cite our code in your work where you are using the MATLAB code.

subjugator

SubjuGator 8 on-board software

swarmlab

SmarmLab: a versatile Matlab package for drone swarm simulation.

tech_blog

无人机理论及实践学习心得

temporal_difference_learning_path_planning

When born, animals and humans are thrown into an unknown world forced to use their sensory inputs for survival. As they begin to understand and develop their senses they are able to navigate and interact with their environment. The process in which we learn to do this is called reinforcement learning. This is the idea that learning comes from a series of trial and error where there exists rewards and punishments for every action. The brain naturally logs these events as experiences, and decides new actions based on past experience. An action resulting in a reward will then be higher favored than an action resulting in a punishment. Using this concept, autonomous systems, such as robots, can learn about their environment in the same way. Using simulated sensory data from ultrasonic sensors, moisture sensors, encoders, shock sensors, pressure sensors, and steepness sensors, a robotic system will be able to make decisions on how to navigate through its environment to reach a goal. The robotic system will not know the source of the data or the terrain it is navigating. Given a map of an open environment simulating an area after a natural disaster, the robot will use model-free temporal difference learning with exploration to find the best path to a goal in terms of distance, safety, and terrain navigation. Two forms of temporal difference learning will be tested; off-policy (Q-Learning) and onpolicy (Sarsa). Through experimentation with several world map sizes, it is found that the off-policy algorithm, Q-Learning, is the most reliable and efficient in terms of navigating a known map with unequal states.

the-formation-of-fixed-wing

thesis

torpedoauv

A custom designed autonomous underwater vehicle. Autonomous localization, Trajectories and Control.

tortuga

Robotics @ Maryland Autonomous Underwater Vehicle

trajectoryplanning

四自由度码垛机器人轨迹规划算法-采用NSGA-II、7次B样条

trajopt

A trajectory optimization library for Matlab

trajplanning

TrajPlan aim to compute a collision free trajectory between two robot posture

trick

Trick Simulation Environment. Trick provides a common set of simulation capabilities and utilities to build simulations automatically.