A flexible and dynamic mission planning architecture for UAV swarm coordination

Abstract

Abstract-In this paper a scalable and flexible Architecture for real-time mission planning and dynamic agent-to-task assignment for a swarm of Unmanned Aerial Vehicles (UAV) is presented. The proposed mission planning architecture consists of a Global Mission Planner (GMP) which is responsible of assigning and monitoring different high-level missions through an Agent Mission Planner (AMP), which is in charge of providing and monitoring each task of the mission to each UAV in the swarm. The objective of the proposed architecture is to carry out high-level missions such as autonomous multiagent exploration, automatic target detection and recognition, search and rescue, and other different missions with the ability of dynamically re-adapt the mission in real-time. The proposed architecture has been evaluated in simulation and real indoor flights demonstrating its robustness in different scenarios and its flexibility for real-time mission re-planning and dynamic agent-to-task assignment.

A Real-Time 3D Path Planning Solution for Collision-Free Navigation of Multirotor Aerial Robots in Dynamic Environments

“…To achieve a fully autonomous operation, a large number of additional components, which are out of the scope of this paper, have been used. These additional components are: perception and state estimation, Sanchez-Lopez et al [35], Bavle et al [4]; control, Pestana et al [24], Olivares-Mendez et al [23]; mission plan specification, Molina et al [19,20]; multi-robot mission planning, Sampedro et al [31]; and human-machine interfaces, Suárez Fernández et al [40], among others.…”

“…The previous version of the here proposed path planner, described in Sanchez-Lopez et al [37], has been validated thanks to its intensive usage in multiple research projects, including three international competitions, IMAV 2013, Pestana et al [25,27], IARC 2014, Sanchez-Lopez et al [26], and IMAV 2016; and in several applications for search and rescue (see Fig. 21), exploration, and inspection applications among others, Sanchez-Lopez et al [32,33], Sampedro et al [31], Sanchez-Lopez et al [34,36]. Its performance has been demonstrated in applications where multiple aerial robot agents are used as moving obstacles, while in others human beings are employed.…”

Artificial intelligence and game theory controlled autonomous UAV swarms

“…Several recent studies proposed the use of global control mechanisms over swarms of uavs in order to control their actions as they accomplish a given task. For example, centralized mission planners to distribute tasks to uavs are suggested in [35], whereas a global coordination among swarm members is discussed in [10]. A pre-planned 3d distribution of multiple uavs is performed to optimize power used by each aircraft in [2].…”

Concrete Crack Identification Using a UAV Incorporating Hybrid Image Processing

“…Recent advances in unmanned aerial vehicle (UAV) technologies have produced low-cost and high-mobility UAVs, rapidly broadening their real-world civil engineering application [ 1 , 2 , 3 , 4 , 5 , 6 , 7 ]. For example, aerial images taken by UAVs have been used to construct three-dimensional structural models [ 8 , 9 , 10 , 11 ], evaluate road conditions [ 12 , 13 , 14 ], and conduct traffic surveillance and management [ 15 , 16 , 17 ].…”