Research On UGV Patrolling Planning Methodology In Contested Environment

Under ground vehicles(UGVs)patrols have a wide range of applications in the field of intelligence reconnaissance and battlefield surveillance.How to plan for UGVs patrol missions will greatly affect their effectiveness on the battlefield.This thesis takes the UGVs patrol mission as the background,mainly focuses on different stages planning problems of the UGVs patrol,and bases on the planning theory and game theory,carries out research on multimodal planning,position-occupation planning,privacy-preserving planning and adversarial planning.The main contributions of this article are as follows:(1)The modal attributes of UGV’s behavior in the contested environment are comprehensively analyzed,and a multi-modal planning framework based on goal recognition is proposed,which provides a basis for reducing the possibility of goals and plans being recognized by opponents.Under the contested environment,UGVs are the executors of patrol operations,and their actions will be observed by opponents.Chapter 3 analyzes the multi-dimensional attributes of unmanned vehicle actions from the aspects of cooperation and confrontation,analyzes the possibility of the goals and plans being recognized by the opponent according to the planning algorithm,realizes multi-modal planning by controlling the goal and plan.(2)A patrol placeholder planning method based on goal recognition is proposed,and an network interdiction game model is constructed,which effectively improves the interdiction efficiency under different network topologies.With regard to the illegal attack behavior that the opponent may perform on the important goal,the possible attack paths of the opponent are analyzed,and the deployment of patrol forces in advance will reduce the risk to the important goals.Chapter 4 analyzes the goal recognition model.In order to control the goal recognition process,two types of network interdiction game models are constructed,the optimal patrol placeholder planning solutions are obtained by solving the network interdiction problem.(3)A new privacy-preserving planning method based on opponent awareness is proposed,which can generate opponent-aware privacy-preserving plan and effec-tively prevent their privacy from leakage.Simulation experiments verify the effec,tiveness of the method.When UGVs perform patrol missions,they face two main types of opponents,the malicious teammates may obtain some private information of UGVs by sharing information,and the hostile opponent can also actively identify our goal and plan through observation.Chapter 5 analyzes the information leakage that may occur during the planning process,and designs privacy-preserving meth-ods with opponent awareness,which mainly include information sharing restricted task planning methods and observability controlled path planning methods.The re-lated algorithms were verified through indoor UGVs’s experiments,and the privacy leakage are analyzed.(4)A unified framework and an integrated planning method for task planning and path planning are proposed.When UGVs are patrolling,real-time online task planning and path planning based on situational information are required.Chapter 6 analyzes the close correlation between task planning and path planning,designs a integrated planning method for tasks and paths.An experimental analysis is performed to verify the effectiveness of the integrated planning method.