Collaborative Mapping Using Swarm Robotics Swarm autonomy is a moderately new research area inspired from biological system, for example, insect or honey bee groups. It makes a framework comprising out of numerous little robots with basic control components fit for accomplishi
Collaborative Mapping Using Swarm Robot
Collaborative Mapping Using Swarm Robotics
Swarm autonomy is a moderately new research area inspired from biological system, for example, insect or honey bee groups. It makes a framework comprising out of numerous little robots with basic control components fit for accomplishing complex aggregate practices on the swarm level, for example, aggregation, pattern formation and collective transportation. Firstly, people use two techniques such as G-map or Hector map for mapping which takes too much time because these techniques uses only one robot to complete the area.
Mapping in an unknown environment is a critical task in the field of robotics.Our system will work on multiple robots which will generate their own map and at the end it will merge all the maps and create a one single map. Our goal is to save time and to work on those areas where Google maps does not operate. The knowledge areas to be covered using ROS, Python, Artificial Intelligence (AI), PCL (point cloud libraries).
Our objective is to create maps using multiple (3 or 4) robots. The maps created by all the robots will be merged and form into one big single map containing all the maps of the robots. This will save time and even if one of the robots stop working the other can continue in completion of the map.
For this, we need four 2D LIDAR laser and four mobile robots,

Flow chart will show u how our project work.
At the end, a Single Big Map Created of any environment.
| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| 2d Lidar laser | Equipment | 4 | 17500 | 70000 |
| robots etc | Miscellaneous | 5 | 2000 | 10000 |
| Total in (Rs) | 80000 |
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