Title: Distributed asynchronous planning and task allocation algorithm for autonomous cluster flight of fractionated spacecraft

Authors: Jing Chu; Jian Guo; Eberhard Gill

Addresses: Faculty of Aerospace Engineering, Delft University of Technology, Kluvyerweg 1, 2629 HS, Delft, The Netherlands ' Faculty of Aerospace Engineering, Delft University of Technology, Kluvyerweg 1, 2629 HS, Delft, The Netherlands ' Faculty of Aerospace Engineering, Delft University of Technology, Kluvyerweg 1, 2629 HS, Delft, The Netherlands

Abstract: For autonomous cluster flight of fractionated spacecraft, planning and task allocation are important as they bridge the gap between the top-level layer (interpreting inputs from the environment) and the bottom-level layer (local controllers) of the distributed space system. This paper presents an asynchronous distributed algorithm that is able to implement planning and task allocation concurrently, instead of one-by-one. First of all, the planning and task allocation problem is formulated in a generalised way. Then the core algorithm is presented, which consists of iterations between two parts. One is the construction of the list of tasks to be allocated and the assignment on-board each module. The other is the consensus process among different constructions of modules by exchanging local information between neighbours, where deconfliction rules are tailored for asynchronous situations. The former part is based on an auction algorithm, while the latter one takes advantage of a consensus algorithm. The entire process iterates asynchronously between those two parts until the planning and task allocation are agreed by all modules. In this paper simulation results are presented, which demonstrate the performance of the asynchronous algorithm not only when fractionated spacecraft operate under nominal conditions, but also when it experiences network disconnects or new tasks.

Keywords: asynchronous algorithm; task allocation; autonomous cluster flight; fractionated spacecraft; multi-agent systems; MAS; agent-based systems; distributed planning; simulation.

DOI: 10.1504/IJSPACESE.2014.060597

International Journal of Space Science and Engineering, 2014 Vol.2 No.2, pp.205 - 223

Received: 08 Aug 2013
Accepted: 29 Sep 2013

Published online: 22 Apr 2014 *

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