When robots contribute to eradicate the COVID-19 spread in a context of containment

In the era of autonomous robots, multi-targets search methods inspired researchers to develop adapted algorithms robot constraints, and with rising Swarm Intelligence approaches, Robotics became a very popular topic. this paper, problem searching for an exponentially increasing number targets in complex unknown environment is addressed. Our main objective propose Robotic target strategy based on Elephants Herding Optimization (EHO) algorithm, namely Robotic-EHO (REHO). The additions were collision-free path planning strategy, velocity limitation, extension multi-target version discrete environments. proposed method has been subject many experiments, emulating infected individuals by COVID-19 context containment within random environments, as well real case study USA. particularity these environments their targets’ dynamic Containment Rate (CR) that we propose. experimental results show REHO reacts much better high CR, early start mission, where robots’ speed higher than virus spread speed.