NDLI: Human control of robot swarms with dynamic leaders

Content Provider	IEEE Xplore Digital Library
Author	Walker, P. Amirpour Amraii, S. Chakraborty, N. Lewis, M. Sycara, K.
Copyright Year	2014
Description	Author affiliation: Robot. Inst., Carnegie Mellon Univ., Pittsburgh, PA, USA (Chakraborty, N.; Sycara, K.) \|\| Sch. of Inf. Sci., Univ. of Pittsburgh, Pittsburgh, PA, USA (Walker, P.; Amirpour Amraii, S.)
Abstract	Controlling a swarm of robots after deployment is difficult, due to the unpredictable and emergent behavior of swarm algorithms. Past work has focused on influencing the swarm via statically selected leaders-swarm members that the operator directly controls-that are pre-selected and remain leaders throughout the scenario execution. This paper investigates the use of dynamically selected leaders that are directly controlled by the human operator to guide the rest of the swarm, which is operating under a flocking-style algorithm. The goal of the operator is to move the swarm to goal regions that arise dynamically in the environment. We experimentally investigated (a) the effect of density of leaders on the ease of human control and system performance, and (b) how restriction of information communicated to the human operator affects the ability to guide the swarm to goal regions. The density of leaders is computed based on an extension of the random competition clustering (RCC) algorithm used in wireless sensor networks to select cluster heads. In particular, we studied the effect of different guarantees of the maximum number of hops in the communication graph from any robot to the nearest leader. Increasing the maximum hop guarantee effectively lowers the density of leaders in the swarm. Our results show that, while there was a large drop in the number of goals reached when moving from a 1-hop to a 2-hop guarantee, the difference between a 2-hop and 3-hop guarantee was not statistically significant. Furthermore, we found that performance was just as good when the information returned to the operator was restricted, showing that operators can still navigate a swarm even when they have imperfect information.
Starting Page	1108
Ending Page	1113
File Size	286144
Page Count	6
File Format	PDF
e-ISBN	9781479969340
DOI	10.1109/IROS.2014.6942696
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-09-14
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Robot sensing systems Robot kinematics Clustering algorithms Vectors Heuristic algorithms Wireless sensor networks
Content Type	Text
Resource Type	Article

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