Development And Path Optimization Of Antiterrorism Robot Control Ststem

As a new type of weapon,anti-terrorism robot has become a trend in today's society.It can effectively combat the strength of terrorist organizations and greatly reduce casualties.Anti-terrorism robots are developing rapidly toward intelligence,but their functions are still relatively simplified,and the ability to adapt to external uncertain environment is general,so the design of an intelligent,sTable and efficient anti-terrorism robot is the future trend of anti-terrorism robots.In this paper,a multi-sensor fusion anti-terrorist robot control system is designed.The control system of the lower computer is divided into four parts: the operation feedback system,the executive operating mechanism,the data monitoring system and the video and audio monitoring system.According to the functional requirements of the lower computer,the main control board circuit based on ARM is designed,including the power module of the anti-terror robot control system,the AD acquisition module,the communication module of the lower computer,the motor driving module,and the walking control of the anti-terror robot.The realization of the main functions such as shooting control and data collection and feedback;In this paper,the communication protocol of each module between host computer and lower computer is established by combining many kinds of sensor technology.The software realization of the information system frame is designed.In this paper,an ant colony hybrid algorithm based on artificial potential field method is proposed for anti-terrorist mobile robot navigation and location.According to the multi-sensor system,the robot's current position information and its own state information can be obtained,and the raster map can be used to simulate the complex environment in reality.Firstly,the mathematical model based on ant colony algorithm is established,and the function of each parameter in ant colony algorithm is analyzed,and the optimal parameters are obtained by MTLAB simulation.Secondly,by introducing a new method of relative target distance and setting middle target point,the traditional artificial potential field method is improved.Finally,combining the advantages of the two algorithms,the paper puts forward In a hybrid algorithm,the artificial potential field method plays a leading role at the initial stage of navigation because of low pheromone concentration,while ant colony algorithm plays a leading role in the middle and late stage with the increase of pheromone concentration.The mathematical model and simulation software design show that the algorithm is superior to the basic ant colony algorithm in path optimization.The anti-terrorist robot control system developed in this paper has been applied in thefield of anti-terrorism and security prevention,and meets the control index of anti-terrorist robot.