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We introduce zePPeLIN, a distributed system designed to address the challenges of path planning in large, cluttered, dynamic environments. The objective is to define a sequence of instructions to precisely move a ground object (e.g., a mobile robot) from an initial to a final configuration in an environment. zePPeLIN is based on a set of wirelessly networked overhead cameras. While each camera only covers a limited environment portion, the camera set fully covers the environment through the union of its fields of view. Path planning is performed in a fully distributed and cooperative way, based on potential diffusion over local Voronoi skeletons and local message exchanging. Additionally, the control of the moving object is fully distributed: it receives movement instructions from each camera when it enters that camera's field of view. The overall task is made particularly challenging by intrinsic errors in the overlap in cameras' fields of view. We study the performance of the system as a function of these errors, as well as its scalability for the size and density of the camera network. We also propose a few heuristics to improve performance and computational and communication efficiency. The reported results include both extensive simulation experiments and validation using a real camera network planning for a two-robot system

zePPeLIN: Distributed Path Planning Using an Overhead Camera Network