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A* ALGORITHM BASICS FOR PATH FINDING & HEURISTICS METHODS : ARTIFICIAL INTELLIGENCE

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 A* ALGORITHM BASICS FOR PATH FINDING A* , widely used  known form of best-first search & path planning algorithm nowadays in mobile robots,games. this is the function for A*,                                     f(n) = g(n) + h(n) g ( n ) is the cost of the path from the start node to n , and h ( n ) is a heuristic function that estimates the cost of the cheapest path from n to the goal This will find cheapest f(n) value in neighbor nodes to archive goal node. check below image  A to B path finding with g(n),h(n),f(n) value In the final level check below image Now we will check the Algorithm // A* Search Algorithm 1. Initialize the open list 2. Initialize the closed list put the starting node on the open list (you can leave its f at zero) 3. ...
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Getting Started with ARGoS Large-Scale Swarm Robot Simulator in Ubuntu

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ARGoS (Autonomous Robots Go Swarming) is a multi-robot simulator designed to support large teams of robots. Its design is pretty different from the design of other simulators. Its most distinctive feature is that the 3D simulated world can be divided in regions, and each region can be assigned to a different physics engine. Furthermore, ARGoS' design revolves around the concept of tunable accuracy. In other words, in ARGoS, everything is a plug-in (robot models, sensors, actuators, physics engines, visualisations, etc) and the user can select which plug-ins to use for an experiment. 
Since different plug-ins have different accuracy and computational costs, users can choose which plug-ins to use for each aspect of the simulation and assign resources only where it matters. This makes the simulation as fast as possible. At the time of writing, ARGoS supports the Swarmanoid robots (foot-bot and eye-bot) and the e-puck. ARGoS supports Linux and Mac OSX. Binary packages are available for Ubuntu, Slackware and Mac OS-X. In addition, a generic binary package can be used for other Linux distributions. 




you can download argos simulator core through this link & follow the installation guide from that page argos core ,

using following link you can easily setup the robots modules  Extensions

lets check what are the robots available  for this simulator

ARGoS-Kilobot The Kilobot is a small, cheap robot widely used in the swarm robotics community. This plugin allows you to simulate the Kilobot in ARGoS. The plugin supports Kilolib, the C interface of the Kilobot. Thus, it is possible to transfer code simulated in ARGoS to the real Kilobots seamlessly.
 using below command you can download above robot source file 
git clone https://github.com/ilpincy/argos3-kilobot.git argos3-kilobot
 
 
ARGoS-Epuck

The E-puck is a small wheeled robot developed for education and research purposes. This plugin allows you to simulate an enhanced version of the E-puck in ARGoS. The extensions comprise a ground sensor, a range-and-bearing board and an Omni-vision module. The plugin supports cross-compilation on the real robot, provided that the robot is equipped with a Linux extension board.

 
 using below command you can download above robot source file  

git clone https://github.com/demiurge-project/argos3-epuck.git argos3-epuck

Example Sources
The example sources are hosted on github: https://github.com/ilpincy/argos3-examples.
To download them, open up a terminal and clone the repository with this command:

git clone https://github.com/ilpincy/argos3-examples.git argos3-examples
 
Follow the instructions in the README file to compile the code.


Robot control code for ARGoS is written in C++. Experiments are configured through an XML file. To run a demo simulation in ARGoS, download the examples from the same URL, uncompress the archive, and run the experiment with the following command:

launch_argos -c xml/diffusion_1.xml
ARGoS provides a 3D simulation environment. In addition, since the physics engines can be chosen by the user, any kind of experiment is possible, including complex self-assembly. Its performance is found to be superior to Stage's. With the full power of four cores on a normal desktop PC, ARGoS can simulate more than 4000 robots in real-time.

check below video for shorter instructions


 
 

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 A* ALGORITHM BASICS FOR PATH FINDING A* , widely used  known form of best-first search & path planning algorithm nowadays in mobile robots,games. this is the function for A*,                                     f(n) = g(n) + h(n) g ( n ) is the cost of the path from the start node to n , and h ( n ) is a heuristic function that estimates the cost of the cheapest path from n to the goal This will find cheapest f(n) value in neighbor nodes to archive goal node. check below image  A to B path finding with g(n),h(n),f(n) value In the final level check below image Now we will check the Algorithm // A* Search Algorithm 1. Initialize the open list 2. Initialize the closed list put the starting node on the open list (you can leave its f at zero) 3. ...
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