Altruistic Relationships for Optimizing Task Fulfillment in Robot Communities

Abstract

This paper introduces the concept of a multi-robot community in which mul tiple robots must fulfill their individual tasks while operating in a shared environment. Unlike typical multi-robot systems in which global cost func tions are minimized while accomplishing a set of global tasks, the robots in this work have individual tasks to accomplish and individual cost functions to optimize (e.g. path length or number of objects to gather). A strategy is presented in which a robot may choose to aid in the comple tion of another robot's task. This type of "altruistic" action leads to evolving altruistic relationships between robots, and can ultimately result in a decrease in the individual cost functions of each robot. However, altruism with respect to another robot must be controlled such that it allows a relationship where both robots are altruistic, but protects an altruistic robot against a selfish robot that does not help others. A quantitative description of this altruism is presented, along with a law for controlling an individuals altruism. With a linear model of the altruism dy namics, altruistic relationships are proven to grow when robots are altruistic, but protect an altruistic robot from a selfish robot. Results of task planning simulations are presented that highlight the decrease in individual robot cost functions, as well as evolutionary trends of altruism between robots.

Altruistic task allocation despite unbalanced relationships within Multi-Robot Communities

“…The controller protects against selfish robots and is guaranteed to increase the level of altruism over time when the other robot reciprocates. See [6] for the stability analysis and extensive treatment of this controller.…”

“…In [6], it was demonstrated that the one-to-one controller successfully improves the individual cost functions of robots in a MRC (see Fig. 2).…”

“…2). Unlike the work from [6], this work considers unbalanced altruistic relationships. An unbalanced relationship exists when robot A cannot, or will not, assist with any of robot B's tasks, but robot B can assist robot A.…”

Centralized and distributed task allocation in multi-robot teams via a stochastic clustering auction

“…Distributed auctions [Andersson and Sandholm 2000;Botelho and Alami 1999;Choi et al 2008;Clark et al 2008;Dias and Stentz 2002;Dias et al 2006b;Gerkey and Mataric 2002;Golfarelli et al 1997;Koenig et al 2007;McLurkin and Yamins 2005;Sandholm 1998;Zheng and Koenig 2009;Zlot and Stentz 2006] involve peer-to-peer redistribution of plans between given subsets of robots, where one of the robots serves as the auctioneer. This class of methods is the primary mechanism for providing intentional coordination between robots.…”

Intelligent Planning and Assimilation of AUV-obtained Measurements within a ROMS-based Ocean Modeling System

“…That is, these techniques can easily be ported to AUVs. One paper ( [12]) discusses robot altruism to optimize task fulfillment. Another, specific to AUVs, discusses cooperative multi-AUV control as it was used in the Autonomous Ocean Sampling Network discussed in Section 3.1.2 [15].…”