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The air pollution has become a major ecological issue. The surpassed pollution levels can be controlled by searching the pollution source. An environmental monitoring unmanned aerial vehicles (UAVs) can address this issue. The challenge here is how UAVs collaboratively navigate towards pollution source under realistic pollution distribution. In this paper, we proposed a novel methodology by using the collaborative intelligence learned from Golden shiners schooling fish. We adopted shiners collective intelligence with the particle swarm optimization (PSO). We used a Gaussian plume model for depicting the pollution distribution. Furthermore, our proposed method incorporates path planning and collision-avoidance for UAV group navigation. For path planning, we simulated obstacle rich 3D environment. The proposed methodology generates collision-free paths successfully. For group navigation of …