We present a vision-based solution to the problem of topology discovery and localization of wireless sensor networks. In the proposed model, a robot controlled by the network is introduced to assist with localization of a network of image sensors, which are assumed to have image planes parallel to the agent's motion plane. The localization algorithm for the scenario where the moving agent has knowledge of its global coordinates is first studied. This baseline scenario is then used to build more

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... complex localization algorithms in which the robot has no knowledge of its global positions. Two cases where the sensors have overlapping and non-overlapping fields of view (FOVs) are investigated. In order to implement the discovery algorithms for these two different cases, a forest structure is introduced to represent the topology of the network. We consider the collection of sensors with overlapping FOVs as a tree in the forest. The robot searches for nodes in each tree through boundary patrolling, while it searches for other trees by a radial pattern motion. Numerical analyses are provided to verify the proposed algorithms. Finally, experiment results show that the sensor coordinates estimated by the proposed algorithms accurately reflect the results found by manual methods.