空氣環(huán)境下移動(dòng)機(jī)器人羽流追蹤方法研究
[Abstract]:Inspired by nature's behavior of tracing chemical information scattered in the air to search for spouses, forage, and avoid enemies, Humans have begun to explore how robots can be fitted with modules such as chemical smoke sensors to simulate the behavior of biological tracing chemical plumes. It is hoped that this kind of robot can replace human in man-made disasters and natural disasters to complete rescue and relief missions. In addition, with the development of globalization, countries are paying more and more attention to social security and national security, so they are developing intelligent robots that can take the place of human resources to carry out search and rescue work, search for contraband and other tasks. It is of great practical significance. At present, chemical plume tracing (Chemical Plume Tracking, (CPT) robot has become the focus of researchers at home and abroad, and relevant research institutions have made outstanding achievements. At present, when CPT robot executes plume tracking task in complex and changeable environment, with the increasing complexity of objective environment, the distribution of plume information becomes more complex, which makes plume tracking more difficult. So in order to fulfill the plume tracking task in complex air environment, CPT robot needs stronger behavior decision ability and autonomous navigation ability to meet the requirement of accuracy. In this paper, the performance of autonomous navigation, the accuracy of speed control and the modeling of robot behavior in plume tracking are studied in this paper. The research work is divided into four parts: (1) using fuzzy Petri nets to model the behavior of CPT robot in the whole plume tracking process, and analyzing the feasibility and correctness of its behavior. (2) to improve the autonomous navigation ability of mobile robot, According to the actual situation of plume tracking process, the traditional A * algorithm is modified, and then the modified A * algorithm is combined with the robot sensor in the circular navigation method. (3) the speed control of driving wheel motor in plume tracking process will affect the accuracy of plume tracking task of CPT robot. Therefore, this paper chooses the fuzzy RBF neural network PID off-line learning method to realize the speed control of robot drive wheel motor, and achieves the practical effect of fast response speed and short adjustment time. (4) build plume tracking robot. Based on AS-4WD mobile robot platform, chemical plume tracking robot is constructed with smoke concentration sensor, ultrasonic sensor and other modules. The model and method in this paper are verified.
【學(xué)位授予單位】:新疆大學(xué)
【學(xué)位級別】:碩士
【學(xué)位授予年份】:2017
【分類號】:TP242
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