TASK1 for EYRC 2020
-
Updated
Jul 29, 2021 - CMake
TASK1 for EYRC 2020
A Bresenham's line based global path planning algorithm. A recursive path planning algorithm was developed that operates on the grid maps represented by a masked array and solves potential looping problems using a state machine-based loop breaking mechanism.
Navigate robots intelligently with MATLAB! Bypass obstacles and find direct paths effortlessly. Visualize every step of your robot's journey. Perfect for beginners and experts alike. Upgrade your robot's intelligence now!
Implementation of "Safe Deep Learning-Based Global Path Planning Using a Fast Collision-Free Path Generator". We present a global path planning method in this project which is based on an LSTM model that predicts safe paths for the desired start and goal points in an environment with polygonal obstacles, using a new loss function (MSE-NER).
Python implementation of Bug2 algorithm to navigate a quadcopter/multirotor in the AirSim simulator.
Implementation of "Safe Deep Learning-Based Global Path Planning Using a Fast Collision-Free Path Generator". We present a global path planning method in this project which is based on an LSTM model that predicts safe paths for the desired start and goal points in an environment with polygonal obstacles, using a new loss function (MSE-NER).
A collection of motion planning projects in Python 3 and YAML
Implementation of Bug Algorithms and Basic Forwards / Inverse Kinematics Equations.
MATLAB implementation of control and navigation algorithms for mobile robots
Implementation of wall-follow , bug0 algorithms
Python implementation of Bug algorithms on 3-wheel omnidirectional and Webots simulation.
Implementation of bug1and bug2 algorithms
Implementation of "Safe Deep Learning-Based Global Path Planning Using a Fast Collision-Free Path Generator". We present a global path planning method in this project which is based on an LSTM model that predicts safe paths for the desired start and goal points in an environment with polygonal obstacles, using a new loss function (MSE-NER).
Implementation of Bug's algorithms for mobile robots in V-REP simulator
Add a description, image, and links to the bug-algorithms topic page so that developers can more easily learn about it.
To associate your repository with the bug-algorithms topic, visit your repo's landing page and select "manage topics."