AUTONOMOUS MULTI-TARGET INTERCEPTION IN DYNAMIC SETTINGS – ON-LINE PURSUER TASK ALLOCATION

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International Journal on Smart Sensing and Intelligent Systems

Professor Subhas Chandra Mukhopadhyay

Exeley Inc. (New York)

Subject: Computational Science & Engineering, Engineering, Electrical & Electronic

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VOLUME 6 , ISSUE 4 (September 2013) > List of articles

AUTONOMOUS MULTI-TARGET INTERCEPTION IN DYNAMIC SETTINGS – ON-LINE PURSUER TASK ALLOCATION

Patricia Kristine Sheridan / Pawel Kosicki / Goldie Nejat * / Beno Benhabib

Keywords : on-line task allocation, autonomous agents, distributed systems, robot motion planning.

Citation Information : International Journal on Smart Sensing and Intelligent Systems. Volume 6, Issue 4, Pages 1,783-1,807, DOI: https://doi.org/10.21307/ijssis-2017-615

License : (CC BY-NC-ND 4.0)

Received Date : 01-August-2013 / Accepted: 18-August-2013 / Published Online: 05-September-2013

ARTICLE

ABSTRACT

In this paper, we present a generic task-allocation methodology for time-optimal, autonomous on-line interception of multiple dynamic targets by a team of robotic pursuers. The proposed novel methodology is applicable to problems consisting of numerous variations of multiple pursuers and targets. The targets are assumed to be highly maneuverable with a priori unknown, though real-time trackable, motion trajectories. Guidance theory is employed to allow each of the pursuers to navigate autonomously towards its allocated target. Numerous simulations and experiments have verified that the proposed methodology is tangibly efficient in dynamic (one-to-one) re-pairing of pursuers to targets for minimum total overall interception time.

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