Multi-robot collaboration for robust exploration

Rekleitis, Ioannis; Dudek, Gregory; Milios, Evangelos

doi:10.1109/robot.2000.845150

Cited by 125 publications

(121 citation statements)

References 64 publications

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“…The moving group stops after several steps and becomes a landmark for the others that take on the role of moving robots. In Grabowski et al (2000), only one robot is allowed to move while the others act as immobile landmarks, while in Rekleitis et al (2001) just one robot remains stationary while the rest of the group navigates. These approaches either require synchronous communications between all members of the team or a central processing unit taking care of the synchronization.…”

Section: Multi-robot Localizationmentioning

confidence: 99%

Collective decision-making based on social odometry

Gutiérrez

Campo

Monasterio-Huelin

et al. 2010

Neural Comput & Applic

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In this paper, we propose a swarm intelligence localization strategy in which robots have to locate different resource areas in a bounded arena and forage between them. The robots have no knowledge of the arena dimensions and of the number of resource areas. The strategy is based on peer-to-peer local communication without the need for any central unit. Social Odometry leads to a self-organized path selection. We show how collective decisions lead the robots to choose the closest resource site from a central place. Results are presented with simulated and real robots.

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Section: Multi-robot Localizationmentioning

confidence: 99%

Collective decision-making based on social odometry

Gutiérrez

Campo

Monasterio-Huelin

et al. 2010

Neural Comput & Applic

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“…Similarly, in [11], only one robot moves, while the rest of the team of small-sized robots forms an equilateral triangle of localization beacons in order to update their pose estimates. Another implementation of cooperative localization is described in [23,24]. In this approach a team of robots moves through the free space systematically mapping the environment.…”

Section: Related Workmentioning

confidence: 99%

“…Other sensors estimate the bearing of the observed robot such as the omnidirectional video cameras used in [13,9], or both the distance and relative bearing, with stereo vision and active lighting in [3], and vision and laser range scanners in [2]. Finally, sensors are able to estimate even the orientation of the observed robot, in addition to the distance and relative bearing [15,24].…”

Section: Related Workmentioning

confidence: 99%

Propagation of Uncertainty in Cooperative Multirobot Localization: Analysis and Experimental Results

Roumeliotis¹,

Rekleitis²

2004

Autonomous Robots

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Abstract. This paper examines the problem of cooperative localization for the case of large groups of mobile robots. A Kalman filter estimator is implemented and tested for this purpose. The focus of this paper is to examine the effect on localization accuracy of the number N of participating robots and the accuracy of the sensors employed. More specifically, we investigate the improvement in localization accuracy per additional robot as the size of the team increases. Furthermore, we provide an analytical expression for the upper bound on the positioning uncertainty increase rate for a team of N robots as a function of N , the odometric and orientation uncertainty for the robots, and the accuracy of a robot tracker measuring relative positions between pairs of robots. The analytical results derived in this paper are validated both in simulation and experimentally for different test cases.

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“…The task of scheduling a meeting between robots that are in constant communication has been addressed by several authors [6], [7], [8] in context of multi-robot exploration. This problem is quite different from our present work since communication makes many synchronization issues straightforward.…”

Section: Related Workmentioning

confidence: 99%

Multi-robot exploration and rendezvous on graphs

Meghjani

Dudek

2012

2012 IEEE/RSJ International Conference on Intelligent Robots and Systems

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Abstract-We address the problem of arranging a meeting (or rendezvous) between two or more robots in an unknown bounded topological environment, starting at unknown locations, without any communication. The goal is to rendezvous in minimum time such that the robots can share resources for performing any global task. We specifically consider a global exploration task executed by two or more robots. Each robot explores the environment simultaneously, for a specified time, then selects potential rendezvous locations, where it expects to find other robots, and visits them. We propose a ranking criterion for selecting the order in which potential rendezvous locations will be visited. This ranking criterion associates a cost for visiting a rendezvous location and gives an expected reward of finding other agents. We evaluate the time taken to rendezvous by varying a set of conditions including: world size, number of robots, starting location of each robot and the presence of sensor noise. We present simulation results to quantify the effect of the aforementioned factors on the rendezvous time.

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Multi-robot collaboration for robust exploration

Cited by 125 publications

References 64 publications

Collective decision-making based on social odometry

Collective decision-making based on social odometry

Propagation of Uncertainty in Cooperative Multirobot Localization: Analysis and Experimental Results

Multi-robot exploration and rendezvous on graphs

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