Path4J - Little Prince Robot Simulator
 | Path4j is an easy to extend, highly graphical, easy to use 2D robot simulator, that is specialized for path planning algorithms. It can be used in testing various robotic algorithms, and it has already being used for the comparison of some path planning algorithms like RRT, RRTConnect, PRM, RboT. - WebStart : Path4j.jnlp. - This project is also served in Path4j@SourceForge. |
How to Run
From sourceforce.net you can get all of the files of Path4J. However, to run the program using Web Start may be a better option. Just click this link and open the path4j.jnlp file with Web Start. For more information consult java.sun.com.
As the program starts there are three steps for running a simulation successfully.
- First download an example below. Extract it.
10Robots-RboT - In the program there is a button named “Simulator”. Click this button, and “Load”. It will ask for “simulation.xml” file. Go to the path of extracted directory, and select the file. So the simulation is loaded.
- Now loading the controller. Again in the main window, select “Planner”, and press “Load”. Go to the folder, in which you selected the “simulation.xml”, then follow into one of the folders in this folder. Select “executer.xml”. Do not forget to press APPLY button at the bottom of this frame, Planner frame!
- When both simulator, and planner is loaded, it is now time to run. Just click “Start” in the main window. According to type of controller, movement of the robots may start immediately, or in a delay.
- When a simulation finishes, to re-run the same simulation, go to Simulator frame, and press reload. Then go to Planner frame, and press reload, then APPLY. So press “Start” to run the same simulation again.
- For more, do not hesitate to ask questions to my sourceforge.net mail account. Thank you :)
Path Planning
Path planning problems arise in many different fields such as; robotics, assembly analysis, virtual prototyping, pharmaceutical drug design, manufacturing, and computer animation. Path planning algorithms aim to solve problems that involve computing a continuous sequence, a path, of configurations between an initial and goal configuration. Planning of a path involves some constraints, such as computing a collision-free path.
The path planning algorithm to be used is generally dependent on the problem at hand. Some algorithms require the environment to resemble some basic geometric shapes, and some others work effectively only for problems in small number of dimensions. If the problem involves dynamic obstacles, or planning path for more than one agent, the difficulty increases considerably.
