(Georgia Institute of Technology, 2009-05)
Viguria Jimenez, Luis Antidio; Howard, Ayanna M.
In this paper we extend our previous work where the mean of the global cost was used as a performance metric for distributed task allocation algorithms. In this case, we move a step forward and calculate the variance of the global cost. This second parameter gives us a better understanding of the distributed algorithm performance, i.e., we can estimate how much the algorithm behavior diverts from its mean. The normal distribution, computed from the theoretical mean and variance, is shown to be suitable for modeling the global cost. This approximation enables us to compare our algorithm theoretically in different cases.
(Georgia Institute of Technology, 2009-04)
Viguria Jimenez, Luis Antidio; Howard, Ayanna M.
In this paper, a problem, called the initial formation problem, within the multirobot task allocation domain is addressed. This problem consists in deciding which robot should go to each of the positions of the formation in order to minimize an objective. Two different distributed algorithms that solve this problem are explained. The second algorithm presents a novel approach that uses cost means to model the cost distribution and improves the performance of the task allocation algorithm. Also, we present an approach that integrates distributed task allocation algorithms with a behavior-based architecture to control formations of robot teams. Finally, simulations and real experiments are used to analyze the formation behavior and provide performance metrics associated with implementation in realistic scenarios.
(Georgia Institute of Technology, 2008-06)
Williams, Stephen; Viguria Jimenez, Luis Antidio; Howard, Ayanna M.
Recently, it has been discovered that the giant ice sheets covering Greenland and Antarctica have been shrinking at an accelerated rate. While it is believed that these regions hold important information related to global climate change, there is still insufficient data to be able to accurately predict the future behavior of those ice sheets. Satellites have been able to map the ice sheet elevations with increasing accuracy, but data about general weather conditions (i.e. wind speed, barometric pressure, etc.) must be measured at the surface. A mobile, reconfigurable sensor network would allow the collection of this data without the expense or danger of human presence. For this to be a viable solution though, a method must be developed to allow multiple robotic scientific explorers to navigate these arctic environments. Specific technological achievements that must be addressed for deployment of this surface-based mobile science network include estimating terrain characteristics of the arctic environment, incorporating these characteristics into a robot navigation scheme, and using this scheme to deploy multiple robotic scientific explorers to specific science sites of interest. In this paper, we discuss an infrastructure that addresses these issues in order to enable successful deployment of these robotic scientific explorers.
(Georgia Institute of Technology, 2007-11)
Viguria Jimenez, Luis Antidio; Howard, Ayanna M.
In this paper, an analysis of a market-based approach applied to the Initial Formation Problem is presented. This problem tries to determine which mobile sensor should go to each position of a desired formation in order to minimize an objective. In our case, this objective is the global distance traveled by all the mobile sensors. In this analysis, a bound on the efficiency for the market-based algorithm is calculated and it is shown that the relative difference as compared with the optimal solution increases with the logarithm of the total number of mobile sensors. The theoretical results are validated with numerous simulations.