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In this paper we consider the problem of coordinating robotic systems withdifferent kinematics, sensing and vision capabilities to achieve certainmission goals. An approach that makes use of a heterogeneous team of agents hasseveral advantages when cost, integration of capabilities, or large searchareas need to be considered. A heterogeneous team allows for the robots tobecome "specialized", accomplish sub-goals more effectively, and thus increasethe overall mission efficiency. Two main scenarios are considered in this work.In the first case study we exploit mobility to implement a power controlalgorithm that increases the Signal to Interference plus Noise Ratio (SINR)among certain members of the network. We create realistic sensing fields andmanipulation by using the geometric properties of the sensor field-of-view andthe manipulability metric, respectively. The control strategy for each agent ofthe heterogeneous system is governed by an artificial physics law thatconsiders the different kinematics of the agents and the environment, in adecentralized fashion. Through simulation results we show that the network isable to stay connected at all times and covers the environment well. The secondscenario studied in this paper is the biologically-inspired coordination ofheterogeneous physical robotic systems. A team of ground rovers, designed toemulate desert seed-harvester ants, explore an experimental area usingbehaviors fine-tuned in simulation by a genetic algorithm. Our robotscoordinate with a base station and collect clusters of resources scatteredwithin the experimental space. We demonstrate experimentally that throughcoordination with an aerial vehicle, our ant-like ground robots are able tocollect resources two times faster than without the use of heterogeneouscoordination.

Exploiting Heterogeneous Robotic Systems in Cooperative Missions