基于态势图序列的多智能群体意图识别  

Intention recognition for multiple agents based on situation map sequence

作　　者：杜沁龙 霍鑫[1] 郑凯[2] 周典乐 DU Qin-long;HUO Xin;ZHENG Kai;ZHOU Dian-le(Control and Simulation Center,Harbin Institute of Technology,Harbin 150080,China;College of Marine Electrical Engineering,Dalian Maritime University,Dalian 116026,China;College of Advanced Interdisciplinary Studies,National University of Defense Technology,Changsha 410073,China)

机构地区：[1]哈尔滨工业大学控制与仿真中心,哈尔滨150080 [2]大连海事大学船舶电器工程学院,辽宁大连116026 [3]国防科技大学前沿交叉学科学院,长沙410073

出　　处：《控制与决策》2024年第9期2941-2949,共9页Control and Decision

基　　金：国家自然科学基金项目(62373128);国家自然科学基金基础科学中心项目(62188101);黑龙江省自然科学基金项目(LH2021F025)。

摘　　要：智能群体的意图识别是多智能体领域的一个热点问题,在自动驾驶、人机交互及国防军事等领域具有广泛应用.由于智能群体规模及环境内障碍物分布具有不确定性,现有意图识别模型的泛化能力往往有限,鉴于此,提出一种基于态势图序列的意图识别方法,将观测得到的智能群体信息转化为态势图序列,通过态势图序列训练识别模型,从而降低模型对智能体数量的敏感程度.针对含有障碍物的环境,提出阻碍态势的生成方法,从而提高模型对环境变化的适应能力.此外,为降低对专家知识的依赖,采用卷积神经网络估计各个智能体的斥力因子.最后,与其他几种意图识别方法对比并进行消融实验以验证所提出方法的准确性和泛化能力.Intention recognition for multiple agents is an important problem in multi-agent systems,and is widely used in autonomous driving,human-machine interaction and military field.Due to the uncertainty in the scale of multiple agents and the distribution of obstacles,the generalization ability of a current intention recognition model is limited.To reduce the sensitivity of the model to the number of agents,an intention recognition algorithm based on a situation map sequence is proposed.The observed information of multiple agents is converted into the situation map sequence and the model is trained based on the situation map sequence.In order to improve the adaptability of the model,the generating method of the obstructive situation map is proposed for situations with obstacles.In addition,in order to reduce the dependence on expert knowledge,the repulsive field factor is estimated using convolutional neural networks.Finally,the proposed method is compared with other methods and ablation experiments are conducted.The accuracy and generalization ability of the proposed algorithm are verified by the results.

关 键 词：运动态势图 意图识别 多智能体系统 深度学习 群体意图 长短时记忆网络 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]