<p>Target search in an unknown environment is a major challenge in disaster relief, hazardous areas, finding leak sources, and surveillance. This paper proposes an Evolving Robotic Dragonfly Algorithm (ERDA) to conduct the target search using a multi-robot team. It works as the distributed control mechanism for the robots. The swarm behaviors of dragonflies in the Dragonfly Algorithm (DA) are improved to solve the multi-robot target search problem. The robot that exhibits the best fitness acts as the leader of the team. The leader robot utilizes the gradient information to evolve the search direction towards the target. ERDA employs an adaptive inertia weight to improve the diversity in the team. The enemy-eluding behavior of DA is adapted to support obstacle avoidance. These factors enhance the performance of the proposed algorithm. The ERDA is rigorously evaluated and compared with existing algorithms. Experiments are conducted in simple and cluttered environments with varying count of obstacles. Also, experiments are carried out with varying number of robots and different environment sizes to study the efficiency and effectiveness of the proposed method. ERDA improved the success rate by 7.41% and reduced the mean iteration count by 53.29% in the cluttered environment. The results obtained indicate that ERDA exhibits better performance than the existing methods.</p>