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a b s t r a c tSource localization is critical to ensuring indoor air quality and environmental safety. Although considerable research has been conducted on source localization in steady-state indoor environments, very few studies have dealt with the more challenging source localization problems in dynamic indoor environments. This paper presents a comprehensive particle swarm optimization (CPSO) method to locate a contaminant source in dynamic indoor environments with mechanical ventilation and develops a multi-robot source localization system to experimentally validate the method. Three robots were used to test the presented method in a typical dynamic indoor environment with periodic swinging of the air supply louvers of a cabinet air conditioner. The presented method was validated with two typical source locations, DS (in the downwind zone) and RS (in the recirculation zone). For DS and RS, 15 and 14 experiments out of 15 experiments were successful, with success rates of 100% and 93.3%, and each robot moved an average of 24.4 and 23.6 steps, respectively. The presented method was also compared with the standard particle swarm optimization (SPSO) and wind utilization II (WUII) methods for locating the source at DS. For the SPSO and WUII methods, only 3 and 6 experiments out of 15 experiments were successful, with success rates of 20% and 40% and averages of 33.0 and 38.0 steps, respectively. The experimental results show that the presented method not only has a much higher success rate than the SPSO and WUII methods but also has higher source localization efficiency.

To solve the problem of pollutant source localization in an indoor environment with dynamic mechanical ventilation better, this paper designed and built a 3D source localization system composed of three 3D source localization robots whose sensors can move under control in the height direction (0.5 m–1.5 m). Through adopting the 3D source localization system, we realized the application of the previously developed the improved whale optimization algorithm (IWOA) method in 3D source localization and proposed the 3D_IWOA method. To validate the feasibility of the 3D_IWOA method and compare the performance of the 3D_IWOA method and other three 3D source localization methods (the 3D_SPSO, 3D_WUⅡ, and 3D_IPSO methods), each method repeated 15 independent experiments in a Training-Center under the same conditions, respectively. For locating the periodic source at a height of 1.05 m in the downwind zone of this environment, the numbers of successful experiments of the 3D_SPSO, 3D_WUⅡ, 3D_IPSO, and 3D_IWOA methods were 5, 6, 11, and 13 (the success rates were 33.3%, 40.0%, 73.3%, and 86.7%), respectively. In addition, the means of total steps of the 3D_SPSO, 3D_WUⅡ, 3D_IPSO, and 3D_IWOA methods were 36.29 steps, 35.96 steps, 31.75 steps, and 38.15 steps, respectively.

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