Consensus-Based Decentralized Auctions for Robust Task Allocation

Abstract

This paper addresses task allocation to coordinate a fleet of autonomous vehicles by presenting two decentralized algorithms: the consensus-based auction algorithm (CBAA) and its generalization to the multi-assignment problem, i.e., the consensus-based bundle algorithm (CBBA). These algorithms utilize a market-based decision strategy as the mechanism for decentralized task selection and use a consensus routine based on local communication as the conflict resolution mechanism to achieve agreement on the winning bid values. Under reasonable assumptions on the scoring scheme, both of the proposed algorithms are proven to guarantee convergence to a conflict-free assignment, and it is shown that the converged solutions exhibit provable worst-case performance. It is also demonstrated that CBAA and CBBA produce conflict-free feasible solutions that are robust to both inconsistencies in the situational awareness across the fleet and variations in the communication network topology. Numerical experiments confirm superior convergence properties and performance when compared with existing auction-based task-allocation algorithms.

Intelligent Cooperative Control Architecture: A Framework for Performance Improvement Using Safe Learning

“…In the controls community, many researchers have developed algorithms for task assignment among teams of vehicles under the name of cooperative plan-ning [Alighanbari, 2004, Alighanbari et al, 2003, Beard et al, 2002, Berman et al, 2009, Cassandras and Li, 2002, Castanon and Wohletz, 2009, Choi et al, 2009, Ryan et al, 2004, Saligrama and Castañón, 2006, Wang et al, 2007. As the name suggests, these methods use an existing world model for planning vehicles task assignment.…”

“…Their approach addresses the problem of maintaining a predefined distribution of robots on a set of locations, yet does not support time varying distributions. Choi et al [2009] used a distributed auction-based approach for task assignment among agents. They bounded the sub-optimality of their solution, yet extending their work to stochastic models is still an open problem.…”

“…For large UAV mission planning scenarios, however, running value iteration is not feasible. Therefore the consensus based bundle algorithm (CBBA) [Choi et al, 2009, Redding et al, 2010a provides the solution. CBBA is a fast algorithm for task assignment among UAVs that uses a deterministic model of the system.…”

“…Many cooperative control algorithms have been designed to address these and other, related issues such as humans-in-the-loop, imperfect situational awareness, sparse communication networks, and complex environments [Beard et al, 2002, Casal, 2002, Choi et al, 2009, Ketan Savla, 2008, Olfati-Saber et al, 2007, Ren et al, 2007, Saligrama and Castañón, 2006, Wang et al, 2007, Xu and Ozguner, 2003]. While these methods had success in a variety of simulations and some focused experiments, there remains room to improve overall performance in real-world applications.…”

“…[Alighanbari, 2004, Beard et al, 2002, Casal, 2002, Choi et al, 2009, Olfati-Saber et al, 2007, Ryan et al, 2004, Saligrama and Castañón, 2006, Wang et al, 2007, Xu and Ozguner, 2003]. This paper introduces a novel approach that takes advantage of cooperative planners and domain knowledge to mitigate the risk of learning, reduce the overall sample complexity, and boost the performance of cooperative planners.…”