A large number of tasks, from manufacturing to planetary exploration, have been successfully accomplished using single robot systems. Many of these tasks could be completed faster, more reliably, and on a larger scale using a cooperating team of autonomous mobile robots. However, robots must be able to coordinate their actions before cooperation is possible. This work aims to enable robots with the ability to coordinate their actions for safe navigation in dynamic, unknown environments. Specifically, the work focuses on: 1) the coordination of multiple robots when sensing and inter-robot communication are limited and 2) multi-robot motion planning in dynamic, unknown environments. First, a new coordination platform is introduced - Dynamic Robot Networks - that facilitates centralized robot coordination across ad hoc networks. As robots move about their environment, they dynamically form communication networks. Within these networks, robots can share local sensing information and coordinate the actions of all robots in the network. Second, a fast motion planner called within robot networks is presented. The planner is a probabilistic roadmap (PRM) motion planner augmented with new sampling strategies. These strategies decrease the planner's run time to enable on-the-fly planning - a key requirement for navigation in environments that are unknown a priori and contain moving obstacles. Simulations and real robot experiments are presented that demonstrate: 1) centralized robot coordination across dynamic robot networks, 2) on-the-fly motion planning to avoid moving and previously unknown obstacles, and 3) autonomous robot navigation towards individual goal locations.


Computer Sciences

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URL: https://digitalcommons.calpoly.edu/csse_fac/77