Code Issues Pull requests Deep Reinforcement Learning for mobile robot navigation in ROS Gazebo simulator. Using Twin Delayed Deep Deterministic Policy Gradient (TD3) neural network, a robot learns to navigate t
Code Issues Pull requests ROS workspace that creates a trajectory for a UAV to follow passing through a set of given waypoints and avoiding a set of given cylindrical obstacles. visualizationuavmotion-planningpath-planningrosapmpixhawkautopilothacktoberfestardupilotwaypointsrvizobstacle-avoidanceapm-planner...
We validate our approach in a simulated multi-robot coordination scenario, where three mobile robots have to reach pre-defined targets while avoiding each other and obstacles in the scene. We also show the generality of our frameworks as applied to different real robotic scenarios. In detail, we...
Code a "naive" obstacle avoiding robot in ROS YOUTUBE VIDEO Description This project was made as a practice for basic ROS concepts such as ros-topics, subscribing, publishing, and simulating robots in Gazebo. The goal was to make a robot: Read data from the 360° LiDAR scanner. Process ...
SihabSahariar / Computer-Vision-Based-Rover-Navigation-Avoiding-Obstacle Star 7 Code Issues Pull requests Using Python and OpenCV to implement a basic obstacle avoidance and navigation on the rover. computer-vision obstacle-avoidance obstacle-detection obstacle-avoidance-robot opencv-object-detection...
Pair the robot with your phone via Bluetooth. Use the app to manually control the robot, toggle obstacle avoidance, line following, or activate custom features. Usage Once powered on, the robot will: Navigate autonomously by avoiding obstacles and following a line. Be controllable via the ELEEGO...
The goal of the game is for player to traverse from one corner of the platform to another, avoiding as many obstacles as possible. There are static obstacles, dynamic obstacles, and unseen obstacles that will appear and collide with the player as time passes. This game is made in Unity. ...
It has achieved results that surpass human-level players in the Atari 2600 game; the algorithm is also suitable for the problem of avoiding obstacles. DQN has two models with the same structure; one is a Q-network and the other is a target Q-network. The parameters of the target Q-...
Heading-error and cross-error reward Simultaneously, in a process to facilitate the autonomous ship using less fuel as far as possible, on the basis of the best path, the reward value is set for its heading and overtaking error when avoiding other obstacles. In this groundbreaking research, ...
Simultaneously, in a process to facilitate the autonomous ship using less fuel as far as possible, on the basis of the best path, the reward value is set for its heading and overtaking error when avoiding other obstacles. In this groundbreaking research, the autonomous vessel was set at a fi...