Research And Design Of Intelligent Robot Based On Multi-Sensor Information Fusion

Due to its advantages like high efficiency,mobility,safe and stabilization,the intelligent robot has become the best alternative for the human who work in high intensity,dangerous and poor working condition.Especially with the advancing of industry 4.0 oriented by intelligent manufacturing,the research and production of intelligent robot is imminent.The traditional robot can perceive the environment by installing the sensor,and can respond in real time according to the environment change,then the effective self-control of robot is achieved.The thesis focus on multi-sensor fusion intelligent robot,and research on the key technologies such as sensor data and processing,data fusion and robot control based on the integrated design.The major contributions of this work are summarized as follows:In view of that the data captured by sensors is large,the corresponding redundancy is high,and error detection is lacking,this thesis focuses processing and extracting the data captured from sensors,and improves the effectiveness and reliability of the data by detecting and eliminating the extra data.Aiming at the problem that the data captured from a single sensor is simplex,lacking of stability,and can not reflect the environmental information completely,the thesis proposes using multi-sensors to collect the data about the environment information,and fusing the preprocessing data.By means of complex inference of the heterogeneous and polytropic information to produce the effect 1+1>2,the control ability of the controller can be enhanced.In real work,high precision and quick response are required for the robot,i.e.the convergence speed is fast,the stability is high and the computation overhead is decreased.So,the paper proses planning the path by ant colony optimization(ACO)algorithm.Transforming the path planning into optimizing the penalty function,the global optimization is achieved by the ant colony optimization(ACO)algorithm.For the adaptive function containing the obstacle restriction and the length of the path information,the safe and shortest path is eventually obtained by ant colony optimization(ACO)algorithm.The results indicate that the multi – sensor information fusion control in this thesis can perceive the change of the surrounding environment,adjust the path planning of robot in real time,and enhance the reliability and work efficiency of the robot effectively.