To address the Coverage Hole (CH) problem in Wireless Sensor Network (WSN) caused by nodes' random deployment or running out of energy, a novel coverage hole detecting algorithm was proposed for wireless sensor networks in this paper. The location information of sensor nodes was used to build the Voronoi diagram for the monitored area. Then the distances between a sensor node and the vertex or edges of the corresponding Voronoi cell were calculated to decide the existence of coverage holes and identify the border nodes. Simulations were conducted to evaluate the performance of the proposed algorithm within different sensing ranges and nodes density. The performance comparison with the Path Density (PD) algorithm shows that the proposed algorithm has about 10% promotion both in average detection time and average energy consumption, which is important for prolonging the network lifetime.

Concerning the breakage warning problem of grid fence, a grid breakage detection algorithm based on improved Harris corner was proposed. As for traditional Harris corner extraction algorithm, the first derivative in vertical and horizontal direction and the corner response function value need to be calculated, and it must be done for each image pixel, which makes this method time-consuming. Therefore, the parameter of gray "similarity" was introduced to demonstrate the gray similarity between pixel and its ambient pixels, through which to filter pseudo corners, reducing the Harris corner extraction time. Then after analyzing the corners' distribution, the breakage areas can be locked. Breakage detection experiments were taken to various fence images taken by robot, and the results indicate that the Harris corner extraction time decreases largely, and the proposed algorithm is effective, meeting the practical application requirements of fence breakage detection.

To reduce the influence of cumulative odometer localization error, an autonomous localization approach for mobile robot based on odometer and Pan-Tilt-Zoom (PTZ) vision was presented. Interrupt S-shaped searching strategy was put forward, as well as a vision localization approach based on finite automaton. The position credibility models of odometer and PTZ vision were established according to their positioning error sources. A localization framework combining odometer and PTZ vision based on real-time position credibility was designed. An application experiment of vision localization and localization using odometer and PTZ vision was carried out. The validity and practicability of the method are confirmed.