| Recently years,because of the fast progress in AI technology,various of mobile robots have begun to appear in people’s lives,such as sweeping robots,bank counter robots and food delivery robots.In the field of electric power systems,to resolve personal security issues arising from manual inspections,inspection robots have been put into using in various substations,power stations and distribution plants.The premise of power inspection robots to achieve different tasks is to own basic positioning function.When the inspection robot in outdoors,people usually use Global positioning technology or Beidou positioning system to obtain its position information.However,if it is in a closed place or indoor environment,the inspection robot cannot receive the signal transmitted by the satellite due to the obstruction of the obstacle,so it cannot complete the positioning.Therefore,it is of great significance to study the positioning technology of indoor power inspection robots without satellite signals.Regarding the positioning of the indoor power inspection robot,this paper firstly uses the least squares method to improve the RSSI ranging algorithm for the problem that the signal which is disturbed by noise during the propagative process and causes the deviation of the RSSI value.Then,on the basis of improved RSSI ranging algorithm,the problem of three circles do not intersect at one point in the traditional trilateral positioning algorithm is corrected,thereby improve the accuracy of the RSSI ranging and positioning method for electric inspection robots.Then,for the problem of limited energy in wireless sensor networks,this paper designs a dynamic event-driven robust set membership fusion estimator for indoor power inspection robot positioning based on RSSI ranging.The estimator is divided into prediction update step and fusion estimation steps,in which each step is transformed into a convex optimization or semidefinite programming problem with dimensional changes,the decoupling method is used to reduce the computational complexity of the algorithm,and the dynamic eventdriven mechanism is designed by reducing the number of patrol robots and surrounding anchor nodes.The frequency of data transmission between wireless sensor networks relieves the communication burden of wireless sensor networks and improves the energy utilization of wireless sensor networks.Finally,the experimental results indicate that the improved RSSI distance location method can improve the location method as well as the location precision.The designed dynamic event-driven mechanism and robust set membership fusion estimator can maintain a high positioning accuracy,while it also has great advantages in terms of energy consumption,communication interaction frequency and computational complexity.Figure [44] Table [10] Reference [67]... |
