“When everybody thinks alike, nobody is thinking much”, is so rightly said. Think out-of-the-box and you potent some innovation or maybe an invention; credits to your gamut. To speak in line with the concept here, swarming population; not always, is a bad idea. How about rescuing some disaster hit zone with swarming intelligent population or maintaining a warehouse with moving, self-operational shelves?? A great idea indeed. Well, this is all about a seemingly new concept of Swarm Robotics. Everybody, in active adolescence or passive maturity may be, must have noticed the movement of ants or similar insects. It is awesomely coordinated and aligned with respect to each other. They accomplish their task collectively by keeping an eye on each other’s movement. This type of coordinated movement in insects is termed as “Swarm” and when this movement is performed by some group of robots then in technical terms it is called as “Swarm Robotics” inspired by colonies of ants and swarms of bees. Simply put, Swarm Robotics is a multi robot system which consists of a large number of simple, physical autonomous robots. It was first coined by Gerardo Beni; professor at University of California and Jing Wang in 1989 in order to impart a notion of swarm intelligence to cellular robotic systems.
Like any other robot, a swarm robot has two main organs; hardware and software. Software is the brain of the system. It gives a simulation environment to the functioning of the robot. In essence, it is the brain of the system. The hardware brings into action, directions simulated by the software. When many such inter-communicable robots are brought to work together, swarming action comes to force.
Introduction to Swarm Intelligence; the wisdom of crowd
Swarm Intelligence is a property of a system or group of systems wherein the members of the group interact locally with each other and the environment in a decentralized manner thereby attaining the desired goal via self-organization. By self-organization we mean the emergence of a global, complex pattern by local level interaction between low-level, simple but autonomous components of the system. The application of swarm intelligence to robotics has conceived to the very idea of swarm robotics. Studies of self-organization in biological species like insects had acted as the biggest inspiration for swarm robotics. Some of the legendary examples are ant colonies, birds flocking, food foraging, schooling of fishes, etc. Let’s have a good look at one of these to find the crux.
Foraging of food by ant colonies: Ants are social insects that do not have eyes or ears. Ants communicate by touch and smell. It sniffs with its antennae to discover whether an intruder is a friend or a foe. They usually set out of their nests in groups for food foraging. Before they leave the nest each day, foragers normally wait for early morning patrollers to return. As the patrollers return and enter their nest, they touch their antennas shortly with the foragers’. Taking this signal as a trigger, the foragers set out for foraging. But not just one contact does the job, foragers require several contacts not more than ten seconds apart before it go out. Foragers use the rate of their encounters with patrollers to tell if it's safe to go out. So, this is how swarm intelligence works, each ant works on its own using local information and without any centralized control. Even if one or two members accidentally run out of the group, the group dynamics remain unaltered and it goes on.
Not only this but have you ever thought how the ant colony does invades exactly the place you dumped your sweets at? This is because individual ants lay a chemical substance called pheromone which attracts other ants.
This brings us to some special characteristics of swarm intelligence:
· De-centralization: De-centralization means there is no central control or leader for the group. The de-centralization of robots makes the individual robots in a robotic swarm autonomous. It reduces complexity of the robotic system to simpler, miniaturized robots. Advantages of decentralization include Simplicity, Modularity, Load variance, and co-operative and co-ordinate abilities.
· Self-organization: Self organization gives the notion of emergent intelligence to swarm robotics. That is the paths to solutions are emergent rather than predefined. Emergent behavior is that behavior of the system which is not the property of any of its components but emerges due to the interactions among the components of a system. Self-organization is based on feedback or errors to provide the swarm with flexibility and robustness as in-
o Positive feedback (amplification)
o Negative feedback (for balancing)
o Amplification of fluctuations (random walks, errors)
· Parallel Distribution: The parallel distribution of tasks in the system helps in enhancing its functional capability. Instead of a highly intelligent robot, the functional complement of multiple robots with low-level intelligence has attracted a lot of researchers.