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In the context of fire incidents within buildings, efficient scene perception by firefighting robots is particularly crucial. Although individual sensors can provide specific types of data, achieving deep data correlation among multiple sensors poses challenges. To address this issue, this study aims to explore a fusion approach integrating thermal imaging cameras and LiDAR sensors to enhance the perception capabilities of firefighting robots in fire environments.

Prior to sensor fusion, accurate calibration of the sensors is essential. This paper proposes an extrinsic calibration method based on rigid body transformation. The collected data is optimized using the Ceres optimization algorithm to obtain precise calibration parameters. Building upon this calibration, a sensor fusion method based on coordinate projection transformation is proposed, enabling real-time mapping between images and point clouds. In addition, the effectiveness of the proposed fusion device data collection is validated in experimental smoke-filled fire environments.

The average reprojection error obtained by the extrinsic calibration method based on rigid body transformation is 1.02 pixels, indicating good accuracy. The fused data combines the advantages of thermal imaging cameras and LiDAR, overcoming the limitations of individual sensors.

This paper introduces an extrinsic calibration method based on rigid body transformation, along with a sensor fusion approach based on coordinate projection transformation. The effectiveness of this fusion strategy is validated in simulated fire environments.

Educational accountability and student achievement polarization, which result in high dropout rates, pose significant challenges and pressures on teachers' pedagogical leadership. Whether pedagogical leadership, which originates in the Western educational environment, can significantly improve student achievement in Chinese high schools remains unclear. This concept has not yet been fully explored in the Chinese educational environment, and its direct impact on student achievement and the mediating role of English teaching methods remain to be investigated. However, existing research has concentrated on the effectiveness of principals' pedagogical leadership, with variations in teachers' pedagogical leadership practices. Many reform measures have been implemented in China to improve student achievement, but past educational practices have analyzed the impact on student achievement from a single instructional leadership, school capital or teaching method perspective. Furthermore, there is a lack of multidimensional and systematic assessments of the direct effects of teacher pedagogical leadership on student achievement and the mediating effects of English teaching methods.

To address this gap, this study analyzed the impact of teachers' pedagogical leadership on student achievement and the mediating effect of English teaching methods with the support of the theory of action for teacher leadership, specifically using pedagogical leadership and English teaching methods models.This study conducted a questionnaire survey of 968 participants in Taian City, China, and quantitatively analyzed the data using SmartPLS structural equation modeling (SEM).

This study revealed that pedagogical leadership has a positive direct effect on student achievement. Meanwhile, among the four mediating factors, the Direct Method, Audio-Lingual Method and Communicative Language Teaching had significant mediating effects.

This study shows that the effective use of academic and professional capital allocation in pedagogical leadership, combined with effective measures of using multiple effective English teaching methods, helps achieve high-quality student achievement.