Graph-based modeling and non-decoupling solution for distributed cooperative mission planning

This paper addresses the problems of autonomous task assignment and path planning for a fleet of heterogeneous unmanned aerial vehicles in cooperative mission. In previous work many algorithms almost run on centralized architecture and handle the task assignment decoupling with the path planning. This may result in poor solutions. Therefore, this paper investigates a novel integrated solution for UAV to perform multiple consecutive tasks cooperatively on multiple ground targets based on distributed planning architecture. In a given scenario, the heterogeneous vehicles have different capabilities, kinematic constraints, and fuel constraints. Furthermore, the task has other constraints, such as task execution orders, UAV conflict free constraints, etc. This paper presents details of the non-decoupling solution which produces optimal assignment and trajectories for several given scenarios. The performance of the algorithm is compared to that of some previous methods in real-time simulation environment. The simulations results show the viability of the non-decoupling approach, and the non-decoupling solution has an advantage over hierarchical algorithms, and the distributed architecture improves the operation efficiency of the algorithm and the robustness of the UAV.

[1]  Ningfei Wang,et al.  Cooperative task assignment of multiple heterogeneous unmanned aerial vehicles using a modified genetic algorithm with multi-type genes , 2013 .

[2]  Prithviraj Dasgupta,et al.  Multirobot Task Allocation with Real-Time Path Planning , 2013, FLAIRS.

[3]  Jonathan P. How,et al.  COORDINATION AND CONTROL OF MULTIPLE UAVs , 2002 .

[4]  Carmel Domshlak,et al.  Integrating Task and Motion Planning for Unmanned Aerial Vehicles , 2014 .

[5]  M. Pachter,et al.  Complexity in UAV cooperative control , 2002, Proceedings of the 2002 American Control Conference (IEEE Cat. No.CH37301).

[6]  Emilio Frazzoli,et al.  Efficient Routing Algorithms for Multiple Vehicles With no Explicit Communications , 2009, IEEE Transactions on Automatic Control.

[7]  Raja Sengupta,et al.  A Resource Allocation Algorithm for Multivehicle Systems With Nonholonomic Constraints , 2007, IEEE Transactions on Automation Science and Engineering.

[8]  Alborz Geramifard,et al.  Cooperative Mission Planning for Multi-UAV Teams , 2015 .

[9]  Farid Kendoul,et al.  Survey of advances in guidance, navigation, and control of unmanned rotorcraft systems , 2012, J. Field Robotics.

[10]  S. Rasmussen,et al.  Tree search algorithm for assigning cooperating UAVs to multiple tasks , 2008 .

[11]  Eunmi Oh,et al.  An Integral Framework of Task Assignment and Path Planning for Multiple Unmanned Aerial Vehicles in Dynamic Environments , 2013, J. Intell. Robotic Syst..

[12]  Tal Shima,et al.  Integrated task assignment and path optimization for cooperating uninhabited aerial vehicles using genetic algorithms , 2011, Comput. Oper. Res..

[13]  L. Dubins.  On Curves of Minimal Length with a Constraint on Average Curvature, and with Prescribed Initial and Terminal Positions and Tangents , 1957 .