An extension of consensus-based auction algorithms for decentralized, time-constrained task assignment

Abstract

This paper addresses the multi-target, multi-task assignment problem for unmanned vehicles by presenting the decentralized Extended Consensus-Based Bundle Algorithm (ECBBA). The algorithm converges to conflict-free feasible solutions; furthermore, the algorithm allows local "pop-up" targets to be added and re-converges to a solution without resolving the entire optimization. A method to limit the communication network around targets is introduced. Limiting the communication is shown, through simulation, to produce solutions commensurate with full communication (within 2%) with the added benefit of reduced communication across the network.

Column generation for a UAV assignment problem with precedence constraints

“…Ofttimes approximation methods are used for practical situations due to the need for speed. One possible choice for a distributed approximation is [18], but further work would be needed to include precedence constraints (see [19]).…”

Boolean Networks-Based Auction Algorithm for Task Assignment of Multiple UAVs

“…The CBBA and the extended algorithms have demonstrated its advantage in TA and achieved the convergence to conflictfree assignment [12][13][14][15][16]. In addition, the demonstration for mathematical features of Boolean network using semitensor product theory is addressed in many papers [17,[19][20][21][22].…”

“…As an improved auction algorithm, the consensus-based bundle algorithm (CBBA) is developed by combining the bundle method with the consensus approach. Many extended algorithms of CBBA demonstrate its advantage in TA field [6,[12][13][14][15]. According to the main components, there are two phases of CBBA.…”

“…The consensus algorithm of CBBA achieves by look-up table approach. It is essentially empirical method, although the original and extended CBBA methods can achieve the convergence to conflict-free assignment [14][15][16]. This manner cannot reveal the logical relation between the information vectors and decision actions.…”

Scaling Laws for Consensus Protocols Subject to Noise

“…It turns out that many sophisticated network coordination tasks can be either entirely reduced to consensus or have decentralized solutions where the consensus iteration plays a key role; we mention formation control [21], [30], [29], [23], distributed optimization [37], [19], coverage control [9], [34], distributed task assignment [5], [18], networked Kalman filtering [3], [35], [1], [31], cooperative flocking/leader-following [10], [20], among many others.…”