TY - JOUR
T1 - A Distributed Framework for Real Time Path Planning in Practical Multi-agent Systems
AU - Abdelkader, Mohamed
AU - Jaleel, Hassan
AU - Shamma, Jeff S.
N1 - KAUST Repository Item: Exported on 2020-10-01
Acknowledgements: Research supported by funding from KAUST.
PY - 2017/10/19
Y1 - 2017/10/19
N2 - 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.
AB - 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.
UR - http://hdl.handle.net/10754/626060
UR - http://www.sciencedirect.com/science/article/pii/S2405896317315185
UR - http://www.scopus.com/inward/record.url?scp=85031812756&partnerID=8YFLogxK
U2 - 10.1016/j.ifacol.2017.08.1035
DO - 10.1016/j.ifacol.2017.08.1035
M3 - Article
SN - 2405-8963
VL - 50
SP - 10626
EP - 10631
JO - IFAC-PapersOnLine
JF - IFAC-PapersOnLine
IS - 1
ER -