Control of heterogeneous robot networks for assistance in search and rescue tasks (2018)
This project develops a decentralized control strategy for multiple heterogeneous robots oriented to the assistance in search and rescue situations from two complementary perspectives, the discrete tasks allocation and the real-time control. For the discrete task allocation through the mission, we present an optimized algorithm based on events, oriented to the minimization of the time required to attend all the victims in the mission environment. This algorithm allows assign to each robot an appropriate task considering that the robots may vary in their capacity for completing each task and also may vary in their moving capabilities. The considered tasks are the mission environment exploration, the victims’ search and identification, the medical supplies delivery to victims unable to move and the evacuation of victims capable to move. It is worth to mention that, through the development of each task and the estimation of its durations, the robots consider optimized routes considering a distance metric based in the breath first search algorithm called flooding distance with 8 neighbors (8NF) which considers only orthogonal and 45 degrees diagonal movements allowing an estimation of the geodesic distance to each point in the map. Regarding to the real-time control laws, they oversee the proper execution of the tasks assigned by the reallocation algorithm respecting the restrictions in the connectivity range, the obstacles avoidance and the fulfillment of each task. The exploration task is made employing an adaptation of the algorithm DisCoverage presented by [16] which employing a Voronoi cells based tessellation considering the arrival time to each point as reference, allows the determination of the map of non-convex spaces as those that may be found in search and rescue situations. The evasion of obstacles and the preservation of the robots’ links is achieved employing an approach of artificial potentials based in the work of [37]. The interest points related to each task tracking is made employing proportional control loops for each agent identifying the route points within the line of sight and considering optimized routes given by the 8NF flooding distance metric. Additionally, there is presented a heuristic reconfiguration algorithm that allows to change the network topology preserving its connectivity for each instant of time. This complete framework allows a team of autonomous robots to bring valuable assistance in certain search and rescue situations where the human teams may be insufficient, and/or the mission conditions may be harmful for the people considering that even if the robots cannot realize paramedical tasks yet, they can complete multiple useful tasks for reducing the effort and risks of the human teams in that kind of situations. The functioning of those algorithms is presented in non-trivial simulations intended to show the behaviors that emerge in the robots.