## 2 Related Work  
Robotic swarms face a variety of challenges such as navigation, communication and collective decision making. These challenges generate in the swarm characteristics robustness and reliability to the system allowing to perform tasks such as exploration and location of targets. In navigation task, there is a great variety of algorithms such as presented in [17] which addresses the characteristics of different algorithms based on swarm intelligence found in nature, such as ant colony, swarm of bees, and wolf pack, among others. The characteristics of the different algorithms generate a great variety of possibilities to choose according to the needs of the challenge. In [18] they use two bio-inspired algorithms; The first algorithm is the particle swarm optimization algorithm, which has good results in exploration work, but sometimes the swarm stagnates in local minima. The second algorithm is the Darwinian particle swarm optimization algorithm, where the swarm is divided into small sub-swarms which share the best solution with the other sub-swarms avoiding being trapped in local minima. As mentioned before, the communication in robotic swarm systems is a research topic that tries to solve problems such as noise due to interference in the environment, loss of information and limitations in the transmission distance and bandwidth of the system. In [19] a low resource consumption communication protocol called RRTLAN is presented which can be implemented in an 8-bit micro controller. An asynchronous communication protocol is shown in [20]; this protocol was tested on robotic platforms that search for a moving target using a multi-robot cooperation strategy. In [21] they use the electrical networks of a collapsed building as a communication channel for a cooperative robotic system that is performing exploration tasks. In [22] a communication protocol called Chopin is proposed and implemented, this protocol was implemented using Robotics Operating System (ROS) in real time. The communication process in a swarm system can be a problem depending on the algorithm implemented, considering that they are systems that manage a great amount of information. Given that a robotic swarm system has a large amount of information coming from each agent of the swarm, a method is required to calculate a consensus value of the acquired information and then a decision is made collectively. In [23] they present a security system for the detection of the intruders which makes a consensus among the sensors located in common areas. In image sensors such as thermal cameras, wireless cameras and security cameras present a large amount of noise due to the environment and lighting, in [24] they use different data fusion techniques implemented in the pixels of the image captured from different cameras. This allows giving greater reliability of the information given by the image resulting from the fusion of the data. On the other hand, platforms designed for search and rescue work need portable energy sources such as batteries or renewable systems. Energy management is very important to allow the platform operates as long as possible without interruptions. In [25] an algorithm is proposed to find an optimal path between two points and using a cross-layer algorithm to improve energy performance. In [26] they propose a system where the transmission of information is not carried out without first reaching a consensus among the different agents. The preliminary consensus is made to eliminate noise faults or malfunction of some sensors and thus achieve energy savings since no redundant information is transmitted. Finally, the victim's detection is the aim of this robotics application. The detection of survivors trapped under debris is a problem in which robotics can help search and rescue teams, unfortunately, there are scenarios that are not allowed to perform frequently tests to evaluate the performance of roboticsystems.