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In complex environments, targets may be affected by factors such as occlusion, changes in lighting, and background interference, resulting in low tracking accuracy and efficiency of mobile robots. In order to ensure the effect of mobile robot target tracking, a mobile robot target tracking method based on multimodal data and Particle filter was proposed. Collect multimodal data of mobile robot targets, and complete the preprocessing of multimodal data of mobile robot targets through steps such as distortion correction, denoising, and enhancement. Extract multimodal data features of mobile robot targets from multiple aspects such as edges, colors, and textures. Taking the extracted features as the research object, the detection results of the mobile robot tracking target are obtained through the training of the Particle filter. Finally, the mobile robot target tracking is realized through the real-time target position update. The experimental results show that in both single target and multi target experimental scenarios, the design method has low tracking error and tracking delay, which can effectively improve the accuracy and efficiency of mobile robot target tracking, and has good mobile robot target tracking performance.