Research On Information Fusion Algorithm Of Mobile Robot Based On Sensor Management

With a large range of advantages, such as robustness, adaptation and high efficiency, a multi-robot system can outperform a single robot and tend to be accepted in many applications where a single robot system has been thought not be suitable. As a result, the multi-robot system has been paid much attention. Nowadays as a rising subject, the cooperative robotics integrate the theories of management seience, soeiology, biology and distributed AI etc. It discusses many topics systematically, such as cooperative behaviors, arehitecture, communication and evolution of the robot system. Based on multi-sensor management, the dissertation gives a through and systematic research on the information fusion of multi-robot system, the tasks distribution and programming of multi-robot coordination. The main contributions are as follows:Firstly, the paper suvreys the developments of multi-source information, cooperative robotics, sensor management and several influential multi-robot systems. We introduce the main research methods, the characteristics and key technology following the main topics about multi-mobile robots. The paper introduces the involved theories too.Then the two improvements are studied on the fusion algorithm. On the one hand, the effect of DSmT fusion algorithm depends on the general basic belief assignment called gbba. The gbba is obtained by the experience of experts. It's based on their own knowledge and easy to cause subjectivity and conflict. The Rough Set Theory needs only sensor data without any subjective information to sum up the inter link between the data. Integreting RST theory and DSmT theory, an objective algorithm on gbba has no difficulty to establishied with the summarized character on data of RST. It will provide an objective basis for the further reasoning and fusion. On the other hand, compared with the DST theory, DSmT theory can resolve the conflict evidences in the fusion information successfully. But DSmT theory brought the problem about "explosion of focus elements". It results an increasing calculation in the fusion greatly. Taking into account the excellent mathematics foundation of DST theory and good fusion result with low conflict situations, DST-DSmT intelligent algorithm is presented in the paper to integrate the advantages of both theories. During the conversion process between DST and DSmT fusion algorithm, an approach processing the conflict focus enlements is given. The method takes full advantage of the conflict in the original information to reflect the information provided by the conflict focues enlements fully.It would decrease the impact on the final fusion result.In order to make the best use of multi-source fusion system, the sensor management becomes an important part of data fusion system.Firstly, considering the distribution of sensors on the robot, different information sources have different reliability and impact in the fusion. The concept of Measurement of Evidence Support, MES is proposed in the paper. The correlation of the focus elements is fully taken into account to determine the core of the information sources in the multi-source system. It has avoided the limitation just depending on the average of the general basic belief assignment to make decisions. A distance is obtained according to the relationship between every information source and the core of the sources in the multi-source system. Some sensors which are irrelevant or have little effect in the fusion have been filted to greatly reduce the number of the sensor in the fusion. Therefore the computation complexity is reduced sharply as well. There exists a great deal of uncertain information in the multi-source information fusion system. An objective function, constraints and optimization function are established with linear methods. The decision about the sensors in the system will be obtained with the optimization method. At the same time the possiblity of the correct fusion result will be improved.Based on the above studies, the collaborative exploration strategy for dynamic partitioning is proposed on multi-robot system. A modular hybrid structure for practical application is designed and made applicable theoretic methods for behavior management, behavior process and behavior decision to the structure.A Layered hybrid architecture for multi-task coordiantion is designed. And the task coordinate flow is given to the multi-robot system. Each robot has its own motion occording to the coordination mechanism, and the multi-task coordination mechanisms make the autonomy of the robot task allocation come to reality. When the robot has completed the task, or can not continue its task, the robots can be self-consultation to get the maximum benefits according to the change degreee of the uncertainty. It's effective to avoid too many robots putting togenther their focus on the same sub-task, which will lead to intensification of the conflicts.At last, we mend the filter process so as to improve the practicability and reliability. Simulations has been done to prove the practicability and reliability of the method.