- Please install Ubuntu 16.04 or above on your laptop (Cannot verify the sanity of the codes for Windows machine)
- Ensure you have Python3 and pip installed
- Ensure you have basic understanding of Python
- A* path planning algorithm
- Dijkstra path planning
- Obstacle Avoidance and Path Retracing
- RRT Path Planning
Please register at this, before participating, so that we can notify you of interviews, meetings and changes, if any.
The contest is live till 4th March, 2019. You need to submit only code.py file over email to the following email address: spandankumarsahu@gmail.com, with the subject as [Software Selections 2019]<RollNumber>
There will be meetings held for doubts and help, on a weekly basis, the exact date and time will be notified through email.
The results of the contest will be updated on a weekly basis, and will be shared through Swarm Robotics' Facebook page. So please, like and follow the page.
For any queries, doubts or help, please email at: spandankumarsahu@gmail.com or give a call to Haque(7430099555) or Spandan(7477858944).
Clone this repository (either download it, or use this command on a terminal: git clone https://github.com/Swarm-IITKgp/SwarmSoftwareSelections)
In one terminal, enter the following:
chmod +x setup.sh
./setup.sh
The program would prompt you to enter a level. Start with 1 and work your way upto level 6.
In another terminal, run:
python controller.py
If you want to view the simulations, run:
python simulation.py
Your task is to complete up as many functions/levels as possible in code.py and submit your codes to spandankumarsahu@gmail.com. You need not attempt all the levels, but sure, the more the better your chances are to get into the team. Your functions may not be optimal (in some cases, optimality cannot even be guaranteed!). We would solely judge on how you approach the problem and how much effort you've put in! :)
This problem statement comes with a sample (pretty unintelligent!) submission for level 1 problem. We shall be providing sample (again, unintelligent ones!) for higher levels too.
There is really not much to play with. There is only one file named code.py, which you must edit and fill out the functions. You're encouraged to use solutions from the lower levels to solve problems of higher level. You can refer to the documentations in api.py, in case you are unsure about what a command does.
(PS: Please go through the problem description to understand the working procedure)
The file app.py is responsible for maintaining the grid, the position of the bots, handling multiple command requests and so on. The controller.py is responsible for simulating multiple bots, using threads. The code.py file uses functions from api.py to send commands to app.py which then replicates what would happen in the zooids' world. The simulation.py file, constantly fetches the current map and displays it. In order to close it, please press Ctrl+C, on the terminal you run it.
To attempt a different level, just close the terminal processes (using Ctrl+c or Ctrl+z), and follow the run instructions again.
The problem is based on the world of zooids, where you are their master. The world of zooid is a grid of dimension 200 x 200. As in any real world, there are obstacles occupying some portions of the grid. The obstacles are strictly rectangular in shape. Here is a sample image 
Each zooid is capable of some basic locomotion. If the zooid is at a location X in a grid, then a movement of type 1, would take it to the grid marked as 1, a movement of type 2 would take it to the grid marked 2 and so on.
1 2 3
8 X 4
7 6 5
As such, zooids are pretty unintelligent beings. Your mission, should you choose to accept, is to make them intelligent and intelligent as a whole. You would learn what is an agent, what is an objective, what is environment, what is a more constrained environment, what is intelligence and how swarm intelligence works.
The obstacles (you cannot move through obstacles) are marked in the map in black, the moving blue colored objects are your zooids, the green colored regions are the ones you must visit, and the red colored regions are the ones you should avoid (you can go through them, but you will end up paying twice as much in any other traversable cell). At each level, the goal is to visit all the green colored regions in as minimum number of steps as possible.
The first level, is to make zooid Zoozoo aware of his capabilities, and show him that he can walk efficiently. Zoozoo's initial and final position will be known to you, and you have to guide Zoozoo through the grid to his destination. Once you reach the destination, you will be awarded a score. Your goal is to reach the destination with as little score as possible. This is an example of a single agent, single objective system.
The second level, is to make Zoozoo intelligent enough to go through all the green regions at least once. This is an example of a single agent, but multiple objective system.
They say, third's the charm! Zoozoo finally has a friend. They have many green regions to go through, and they should co-operate among themselves to achieve this goal with minimum steps. This is an example of multi-agent, multi-objective system.
Zoozoo and his friend have now wondered into a swarm. There are many more zooids, each equally capable as Zoozoo. And there are still more than one green regions to go through. Can they cooperate as a group? This should teach them something about swarm systems!
Zoozoo and his friend have now been landed into a harsher territory. It's only two of them and they are still to go through the green regions, but now, there are patches of red regions that they should ideally avoid, because each step through the red region is counted as 2 steps. But then, sometimes, it might be necessary to go through the red regions in order to avoid a longer way through the green one. Hmmmm.. they need some intelligence!
Now a swarm of zooids has joined in to help Zoozoo and his friend. This is the beginning of swarm intelligence. Now, do you feel like a God who programmed his creations to intelligence?