Imagine being lost in a desert with a bunch of friends, all of a sudden. Survival will be difficult. You will have mirages, distrust among friends and no means to leave landmarks on the sand. Unable to locate yourself, you will have no means to contact people with maps. The best you can do in such a situation is to stay together in the vicinity of each other and look for food and water. By staying together, you can see more and decrease faulty data; thereby increasing your survival probability. Robots when left to explore the moon encounter the same issues. They do not have a Geo-Positioning System to locate them nor do they have a map. They have faulty sensor readings and might find it difficult to contact a human operator on earth all the time to solve issues on the moon. Since everything looks the same, there are no landmarks to memorise. As they walk around, their battery will also get exhausted. The more we equip the robot outside earth, chances of faults do not decrease, they increase. Therefore, there is a need to make primitive robots capable of autonomous exploration. We prefer sending more than one robot, inspired by the success of the collective strength of insects in harsh environments. This thesis aims at engineering collective behaviour for a group of robots in such resource-less environments like the moon. We expect this collective behaviour to perform searching in time-critical events like earthquake-stricken areas. The thesis is designed to be implemented on legged robots called Zebros. Using communication, they will collectively perform activities such that they appear as one body of tightly coupled autonomous units. We design three distinct algorithms for such missions. Emergent behaviour is expected from the robots running these algorithms. The swarm should collectively choose the best among the possible options without disintegrating into subgroups. (https://www.youtube.com/watch?v=Yf3ToRk7YHY&feature=youtu.be)