Cueing Flight Object Trajectory and Safety Prediction Based on SLAM Technology
DOI:
https://doi.org/10.53469/jtpes.2024.04(05).01Keywords:
SLAM technology, Flying object position prediction, EvolveGCN model, Experimental verificationAbstract
With the rapid development of artificial intelligence and robot technology, SLAM technology, as a key component, has been paid more and more attention. SLAM technology enables robots to autonomously navigate, build maps, and achieve accurate positioning in unknown environments, providing strong support for the autonomy and intelligence of robots and unmanned vehicles. In this paper, the position prediction method of flying object based on SLAM technology and the application of EvolveGCN model in behavior prediction are introduced. First, through the fusion of SLAM technology and liDAR data, we can accurately predict the position and movement trajectory of flying objects, thereby improving the safety and efficiency of the system. Secondly, with the EvolveGCN model, we are able to capture dynamic changes in the environment and achieve accurate predictions of the behavior of flying objects. Through experimental verification, the prediction accuracy of our method has been significantly improved in both simulation and real environment, which indicates the feasibility and effectiveness of the method in practical application, and provides an important reference and technical support for the development of autonomous navigation, aerial surveillance and other fields.
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Copyright (c) 2024 Chao Fan, Weike Ding, Kun Qian, Hao Tan, Zihan Li
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
