@INPROCEEDINGS{Dantu_Berman_Kate_Nagpal_12,
	author={K. Dantu and S. Berman and B. Kate and R. Nagpal},
	booktitle={Intelligent Robots and Systems (IROS), 2012 IEEE/RSJ International Conference on},
	title={A comparison of deterministic and stochastic approaches for allocating spatially dependent tasks in micro-aerial vehicle collectives},
	year={2012},
	pages={793-800},
	keywords={aerospace control;aerospace robotics;microrobots;multi-robot systems;stochastic processes;MAV;crop field;deterministic approaches;microaerial vehicle collectives;pollination activity;resource constrained robots;robotic swarms;spatial distribution;spatially dependent tasks allocation;stochastic approaches;Agriculture;Navigation;Resource management;Robot sensing systems;Stochastic processes},
	doi={10.1109/IROS.2012.6386233},
	ISSN={2153-0858},
	month={Oct},
	abstract = {We compare our previously developed deterministic [7] and stochastic [3], [4] strategies for allocating tasks
        in robotic swarms1 consisting of very large populations of highly resource-constrained robots. We study our two task allocation 
        approaches in a simulated scenario in which a collective of insect-inspired micro-aerial vehicles (MAVs) must produce a specified
        spatial distribution of pollination activity over a crop field. We investigate the approaches' requirements, advantages, and disadvantages 
        under realistic conditions of error in robot localization, navigation, and sensing in simulation. Our results show that the deterministic 
        approach, which requires region-based robot navigation, yields higher task progress in all cases. For robots without such navigation capabilities, 
        the stochastic approach is a feasible alternative, and its resulting task progress is less sensitive to error in localization, error in navigation, 
        and a combination of high error in localization, navigation, and sensing.},
}