Mine Detection using a Swarm of Robots

Abstract

Robotics is an area that is finding its use in every field today owing to the fact that it has proven time and again evolutionary changes that it has brought about. Long gone are the days when the military walked into traps or blindly entered a territory only to get knocked down. With the help of advancements in technology, the military is becoming more capable of doing life endangering operations such as bomb-defusing, fighter pilot aviation and entering enemy territory with much more confidence as it is being backed-up by all the extra help and support that technology is bringing despite the fact that there are many unknown variables involved in such high-risk military operations. Soldiers are humans, they have fears, weaknesses and can never prove to be as reliable as a robot in terms of efficiency as robots have unwavering performance efficiency. Just as the use of unmanned aerial vehicles has entirely changed the narrative of military fighter aviation, for an issue just as big if not more, of landmine detection in any given territory, the use of robots will change things for the better. In a time when human capital has proven to be the biggest asset a nation has, it is only essential that it is safeguarded at every step possible, especially if it also means added benefits. Artificial Intelligence (AI), Mobile robotics and Internet of Things (IoT) are technologies that make it possible to implement a swarm of such robots that can gather information from the surroundings with the help of sensors and send that information back to the operator station, just as any human soldier would do, while also having the added functionality of being able to detect landmines which are explosives planted to destroy troops entering a territory, which are all tasks that a human soldier would usually carry out at the risk of his/her own life. This paper describes in great detail how a swarm of robots could be deployed by the military for tasks that usually have a great chance of casualties, reduce it to zero and prove to be more efficient in doing so.