Abstract
Cooperative behaviors in multi-robot systems emerge as an excellent alternative for collaboration in search and rescue tasks to accelerate the finding survivors process and avoid risking additional lives. Although there are still several challenges to be solved, such as communication between agents, power autonomy, navigation strategies, and detection and classification of survivors, among others. The research work presented by this paper focuses on the navigation of the robot swarm and the consensus of the agents applied to the victims detection. The navigation strategy is based on the application of particle swarm theory, where the robots are the agents of the swarm. The attraction and repulsion forces that are typical in swarm particle systems are used by the multi-robot system to avoid obstacles, keep group compact and navigate to a target location. The victims are detected by each agent separately, however, once the agents agree on the existence of a possible victim, these agents separate from the general swarm by creating a sub-swarm. The sub-swarm agents use a modified rendezvous consensus algorithm to perform a formation control around the possible victims and then carry out a consensus of the information acquired by the sensors with the aim to determine the victim existence. Several experiments were conducted to test navigation, obstacle avoidance, and search for victims. Additionally, different situations were simulated with the consensus algorithm. The results show how swarm theory allows the multi-robot system navigates avoiding obstacles, finding possible victims, and settling down their possible use in search and rescue operations.
Highlights
Natural disasters and wars are some of the worst events that humanity has had and will have to face, since in these kinds of situations it is almost impossible to evacuate people in the affected area, causing many more deaths and having a devasting impact
Taking into account that this rendezvous consensus allows all agents to reach the same position in the space, the step is to guarantee the connection between the agents while the signal control is modified to reach the goal position for each agent based on the approach shown in [11] which in order to solve the problem of maintenance communication, artificial potential functions was performed used to guarantee connectivity and keeping a distance among agents with the aim to avoid collisions
After sub-swarm creation, the consensus and control formation algorithm is performed as shown in Figure 11 as explained previously in this paper the consensus looks for to approach every drone to the victim, reducing the uncertainty of sensing factor over the possible victim
Summary
Natural disasters and wars are some of the worst events that humanity has had and will have to face, since in these kinds of situations it is almost impossible to evacuate people in the affected area, causing many more deaths and having a devasting impact. Multi-robot research has shown a different alternative to solve the aforementioned task, for instance, the advantages of using robotic swarms in exploration tasks is mentioned in [7,8] Advantages such as coverage of a larger area in less time in contrast to the use of a single platform. It is necessary to take into account the control law that allows a swarm to create attraction towards the victims and repulsion towards obstacles and robots in order to avoid collisions This approach is achieved using attractive and repulsive potential functions as shown in [11], among other works that have been made to solve the different challenges that entail the exploration task.
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