一种面向自主与远程驾驶航空系统的意图建模与推理框架
An Intent Modeling and Inference Framework for Autonomous and Remotely Piloted Aerial Systems
AI总结：
本文提出一种面向自主与远程驾驶航空系统的意图建模与推理框架，定义UAS意图数学模型，结合IMM滤波器与注意力Bi-LSTM网络实现意图推理，可辅助地理围栏的未授权飞行防御规划。
摘要：
本文提出了一种意图建模与推理框架，以辅助保护地理围栏免受未授权飞行的防御规划。首先，本文提出了无人机系统（UAS）意图的全新数学定义，引入了关键航路点与关键航路点模式的概念，并将其与运动过程相关联，以完整表征意图。该建模框架包含用于规划飞行器运动序列的UAS任务规划器表示，以及为保护地理围栏而定义的防御规划器表示，适用于存在障碍物的二维与三维环境中的自主、半自主及有人驾驶系统。\n本文通过为安全应用定义意图库来阐释该框架。假设已实现目标的检测与跟踪，以此构建意图推理问题。作为基于深度学习的方法的一部分，本文讨论了决策者目标的多种公式化表述。此外，本文还探讨了用于表征UAS飞行的多模态动态模型，该模型随后被用于通过交互多模型（IMM）滤波器提取特征，以训练意图分类器。最后，作为仿真研究的一部分，本文提出了一种用于意图推理的基于注意力机制的双向长短期记忆（Bi-LSTM）网络。仿真实验在二维与三维环境中验证了该框架的多个方面，包括轨迹生成、雷达测量仿真等。
英文摘要：
An intent modelling and inference framework is presented to assist the defense planning for protecting a geo-fence against unauthorized flights. First, a novel mathematical definition for the intent of an uncrewed aircraft system (UAS) is presented. The concepts of critical waypoints and critical waypoint patterns are introduced and associated with a motion process to fully characterize an intent. This modelling framework consists of representations of a UAS mission planner, used to plan the aircraft's motion sequence, as well as a defense planner, defined to protect the geo-fence. It is applicable to autonomous, semi-autonomous, and piloted systems in 2D and 3D environments with obstacles. The framework is illustrated by defining a library of intents for a security application. Detection and tracking of the target are presumed for formulating the intent inference problem. Multiple formulations of the decision maker's objective are discussed as part of a deep-learning-based methodology. Further, a multi-modal dynamic model for characterizing the UAS flight is discussed. This is later utilized to extract features using the interacting multiple model (IMM) filter for training the intent classifier. Finally, as part of the simulation study, an attention-based bi-directional long short-term memory (Bi-LSTM) network for intent inference is presented. The simulation experiments illustrate various aspects of the framework, including trajectory generation, radar measurement simulation, etc., in 2D and 3D environments.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
