A Distributed Framework for Real Time Path Planning in Practical Multi-agent Systems
Type
ArticleKAUST Department
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) DivisionElectrical Engineering Program
Mechanical Engineering Program
Physical Science and Engineering (PSE) Division
RISC Laboratory
Date
2017-10-19Permanent link to this record
http://hdl.handle.net/10754/626060
Metadata
Show full item recordAbstract
We present a framework for distributed, energy efficient, and real time implementable algorithms for path planning in multi-agent systems. The proposed framework is presented in the context of a motivating example of capture the flag which is an adversarial game played between two teams of autonomous agents called defenders and attackers. We start with the centralized formulation of the problem as a linear program because of its computational efficiency. Then we present an approximation framework in which each agent solves a local version of the centralized linear program by communicating with its neighbors only. The premise in this work is that for practical multi-agent systems, real time implementability of distributed algorithms is more crucial then global optimality. Thus, instead of verifying the proposed framework by performing offline simulations in MATLAB, we run extensive simulations in a robotic simulator V-REP, which includes a detailed dynamic model of quadrotors. Moreover, to create a realistic scenario, we allow a human operator to control the attacker quadrotor through a joystick in a single attacker setup. These simulations authenticate that the proposed framework is real time implementable and results in a performance that is comparable with the global optimal solution under the considered scenarios.Citation
Abdelkader M, Jaleel H, Shamma JS (2017) A Distributed Framework for Real Time Path Planning in Practical Multi-agent Systems. IFAC-PapersOnLine 50: 10626–10631. Available: http://dx.doi.org/10.1016/j.ifacol.2017.08.1035.Sponsors
Research supported by funding from KAUST.Publisher
Elsevier BVJournal
IFAC-PapersOnLineAdditional Links
http://www.sciencedirect.com/science/article/pii/S2405896317315185ae974a485f413a2113503eed53cd6c53
10.1016/j.ifacol.2017.08.1035