In the current context of rapid development of information technology and AI, entertainment interactive robots can play an auxiliary role in fitness training. Intelligent technical services can provide athletes with timely training course information and gamified sports training. Various data will also be uploaded to technical platforms for analysis. This article studies the design of a personalized fitness training system for entertainment interactive robots based on intelligent algorithms. Firstly, this article analyzes the main technologies of photon integrated biosensors, establishes a linear photon integrated biosensor imaging model. Choose to use intelligent algorithms to optimize coverage for wireless sensor networks. This problem is transformed into a mathematical function model, and then the optimal solution is sought through algorithms, effectively reducing the energy consumption of the network and extending its lifespan. The system improves interaction with humans by collecting training action videos, automatically recognizes the types of human training actions, and automatically extracts key postures from training actions for comparison and analysis with standard postures. The practice and research of human–computer interaction have shown that in addition to the actual performance of social robots, the emotional interaction of social robots can also affect people's trust in their abilities.