A three-dimensional space path planning method based on A ∗ algorithm in radiation environment

Path planning is a critical radiation protection strategy designed to minimize radiation exposure for personnel involved in nuclear emergency response. In many practical scenarios, path planning within a radiation environment is inherently a three-dimensional (3D) problem. Existing 3D path planning methods have predominantly targeted robot navigation and UAV flight operations in non-radiation scenarios, typically overlooking radiation dose exposure. However, in nuclear emergency situations, personnel frequently need to perform operational tasks within radiation environments, necessitating strict control over their radiation exposure levels. Consequently, existing 3D path planning methods developed for robots and UAVs may be unsuitable for human operations, underscoring the need for targeted research into 3D path planning specifically for personnel operating in radiation-contaminated environments. 3D path planning in radiation environments faces two primary challenges: accurately modeling the 3D radiation field and developing a path planning approach that concurrently considers both travel distance and radiation dose exposure. To address these challenges, we propose an innovative three-dimensional A* algorithm (TDA) explicitly tailored for radiation environments. Additionally, this study utilizes the standardized Rad-HUMAN voxel model to accurately simulate human anatomy, combined with GPU-based parallel computing techniques to achieve precise and efficient radiation dose assessments during path traversal. Two simulation experiments have been conducted to validate the method’s feasibility and demonstrate the advantages of the proposed path planning method. • A 3D A* algorithm (TDA) is proposed for radiation-aware path planning. • TDA integrates distance and dose rate into a unified radiation-aware cost function. • A human voxel model is employed to enhance organ-specific radiation dose evaluation. • Simulation results confirm the superior performance of the proposed TDA method.