Indoor environments are relatively enclosed spaces. In emergency situations such as hazardous gas leakage, they can pose serious threats to human life and property. Therefore, rapidly and accurately locating the odor source is of great significance for the effective implementation of rescue operations.This paper addresses complex indoor environments with interference sources and proposes a rapid odor source localization method based on a multi-robot cooperative Leader–Follower Shark Smell Optimization algorithm (LF-SSO). The algorithm adopts a leader–follower mechanism, enabling follower robots to track the odor source by following the direction of the leader robot.To validate the performance of the proposed algorithm, two indoor simulation models are constructed. Simulation results show that, in the presence of a single interference source, the LF-SSO algorithm improves the localization success rate by approximately 10%, with the localization error remaining below 0.8 m. When the number of robots exceeds six, the localization success rate reaches 100%.Furthermore, the LF-SSO algorithm demonstrates advantages in both localization success rate and localization time, reducing the robots’ search time and effectively preventing all robots from falling into local optima. It also provides a new solution for the application of active olfaction technology in complex indoor environments.