Research Of Collaborative Network System In Unmanned Aerial And Ground Vehicles

With the rapid development of science and technology and the deepening of social information process,communication technology,computer technology and intelligent control technology have been widely applied to every field of people's life.As the extension and embodiment of modern information technology,the Internet of Things is getting more and more attention.Based on the embedded technology,Zigbee technology and intelligent control technology,combined with wireless sensor networks,intelligent car and Unmanned Aerial Vehicle(UAV),this thesis aims at researching of collaborative network system with unmanned aerial and ground vehicles.It first studied the process of collaboration in the network,and then focused on obstacle avoidance path planning algorithm.It introduced an improved path planning algorithm so that the planned path is more suitable for actual driving of the intelligent car.The collaborative network simulation system described in this thesis can achieve flexible collection of information,real-time monitoring and automatic fault repairing.The system includes the environment sensing modules,the intelligent car module,the UAV information converging transmission module and the information processing and controlling module.According to the demands of the system,this thesis focuses on the mobile ad hoc collaborative network and intelligent obstacle avoidance path planning algorithm.A model of the network,intelligent car body and environmental barriers has been made.In order to achieve the network collaboration and autonomous reparation of node fault with intelligent car,this approach takes the idea of Floyd algorithm into consideration.It not only improves the traditional path planning algorithm in reducing path inflection points by 20%,but also does real-time analysis of the network topology and node status through the information processing and controlling module.The collaborative network simulation system has functions including intelligent car path planning,real-time video transmission,information gathering and remote transmission with UAV,and real-time display and monitoring of network topology.The experiment proves that it meets the functional requirements proposed by the simulation system design,including improving the agility of the node failure response and the flexibility of the environmental awareness network.