A Kind Of Obstacle Avoidance And Fire Fighting Smartcar Based On Particle Swarm Optimization Algorithm

With the increasing of the fire causes, the situations which the firefighters face become more and more complex and changeable. To reduce the difficulty and danger of the fire rescue has become the fundamental starting point of the fire study. In order to reduce the casualties of firemen, the fire fighting smartcars are eagerly expected to replace the firemen to enter the fire field finishing the rescue tasks. For the above reason, this dissertation introduces how to accomplish a fire fighting smartcar. According the design methods of the software and hardware, with the theory of Particle Swarm Optimization (PSO), the following work have been finished.(1) Firstly this dissertation pays close attention to the study and analyses of the PSO using the MATLAB, and the PSO has been determined to the strategy of the path planning.(2) Consequently the concrete measure of the hardware have been clearly taken. Applying the MCS named STC89C52RC, and the infrared obstacle avoidance sensors named E18-D80NK and the Photoelectric tracing sensors named TCRT5000, also and the motor drive chip named L298N, etc., the hardware of the smartcar have been constructed.(3) At the sametime, the source code also have been programmed in the IDE named Keil uvision. Using the download suit named STC-ISP, the joint debugging between software and and hardware have been carried out. Finally, some evaluations, summaries, suggestions on the smartcar have been acquired.