Randomized trial evaluates CPE-Infotaxis for improving search efficiency in nuclear emergencies, highlighting significant advancements.
In nuclear emergency response, minimizing radiation exposure is critical, yet single robots struggle to efficiently locate leakage sources in complex turbulent environments. Multi-robot Infotaxis offers a promising solution but remains vulnerable to radiation-induced sensor failures that introduce false information and corrupt shared beliefs. To address these challenges, we propose the CPE-Infotaxis (Cognitive Probabilistic Entropy Infotaxis) algorithm, in which each robot dynamically adjusts the credibility of received information through relative entropy-weighted social Bayesian estimation, and executes a distributed Infotaxis search strategy based on this assessment, while integrating an exploration-exploitation balancing strategy and an adaptive step-size mechanism to mitigate excessive exploration. The proposed CPE-Infotaxis method is evaluated against both the traditional Infotaxis and PE-Infotaxis algorithms under ideal and fault-detection scenarios. Experimental results show that CPE-Infotaxis improves search efficiency by 40.7% compared to traditional Infotaxis and by 38.7% compared to PE-Infotaxis(Exploration Probability Infotaxis), providing robust technical support for autonomous radioactive leakage source search in nuclear emergency response.
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Zhou et al. (2026) studied this question.
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