Udacity Quadcopter Project
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Updated
Aug 7, 2019 - HTML
Udacity Quadcopter Project
This work basically presents the analytical work for solving the problem "B" of "UPC-2020"
This project is about training a deep neural network to identify and track a target in simulation using Udacity's RoboND drone simulator. 🛸 Applications like this are key to many fields of robotics and the techniques applied can be extended to scenarios like advanced cruise control in autonomous vehicles or human-robot collaboration. 👨🏫
Quadcopter simulation in 3D space
Quadcopter simulation with Simulink
Quadcopter simulation with Webots
3D Simulation of a quadcopter system in MATLAB. Controllable with keyboard input (note: no flight controller implemented)
Quadcopter Project
Quadcopter Control Along with sensor fusion of EEG data along with eye tracking data using the Extended Kalman Filter
Quadrotor (Quadcopter) linear and non-linear controller simulation with SIMULINK MATLAB
This model include; plant,controller,sensor,filter and disturbance models.
An autonomous delivery drone that delivers and returns parcels on landing markers
Low-level autonomous control and tracking of quadrotor using reinforcement learning - Proximal Policy Optimization
Simulation of Quadcopter/Quadrotor Exploration of Unknown Environments using Artificial Potential Field. Uses Vispy for animation
Autonomous Indoor Quadcopter using ROS & Gazebo Simulator | Fall 2019
Multiple quadrotors carrying a flexible hose: dynamics, differential flatness and control
Quadcopter Simulation and Control. Dynamics generated with PyDy.
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