Shepherding with robots that do not compute

Anıl Özdemir, Melvin Gauci and Roderich Groß

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Abstract

We examine the problem solving capabilities of swarms of computation-free and memory‐free agents. Each agent has a single line-of-sight sensor providing two bits of information. The agent maps this information directly onto constant motor commands.

In previous work, we showed that such simplistic agents can solve tasks requiring them to organise spatially (multi‐robot aggregation and circle formation) and manipulate passive objects (clustering).

In the present work, we address the shepherding problem, where the computation-free and memory‐free agents (the shepherds) are tasked to gather and move a group of dynamic agents (the sheep) towards a user defined goal. The shepherds and sheep are modelled as e‐puck robots using computer simulations.

Our findings show that the shepherding problem does not fundamentally require arithmetic computation or memory to be solved. The obtained controller solution is robust with respect to sensory noise, and copes well with changes in the number of sheep.


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10 shepherds herding 20 and 100 sheep using the best controller, and the extended controller.
The modified experiment setup.

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Natural Robotics Lab: investigating robotic systems inspired by nature, and robotic models of natural systems.

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