NeuralNetwork Application for Mobile Robot

NeuralNetwork Application for Mobile Robot is a project focused on applying neural network techniques to real-world robotic navigation and control.

The system demonstrates a mobile robot following a predefined path (black line) using learned behaviors, showcasing stable and responsive movement in physical environments. This highlights the practical application of neural networks in low-level control and perception tasks.

In addition to physical experiments, the project includes simulation of an obstacle restriction method using Webots. These simulations explore how the robot can perceive, avoid obstacles, and adapt its trajectory in a controlled 3D environment.

By combining real-world experiments with simulation, the project provides a comprehensive view of how neural networks can be applied to robot navigation, control systems, and obstacle avoidance.

Check here for details.