Assigning Micro UAVs to Task Tours in an Urban Terrain

Abstract

An optimization algorithm for assigning in realtime multiple unmanned aerial vehicles (UAVs) to task tours is presented and tested as part of a flight demonstration program. The scenario of interest is one where multiple microaerial vehicles are launched from a small UAV in order to investigate selected targets in an urban terrain. For path planning, we use the Dubin's car model so that the vehicles' dynamic constraint of minimum turning radius is taken into account. Due to the prohibitive computational complexity of the coupled path optimization and assignment problem, we solve the problem by ordering a set of tasks based on the Euclidean distance, utilizing a traveling salesman problem solver. We apply upper and lower bounding procedures iteratively on active subsets within the set of feasible group assignments, enabling efficient search of the solution space. The online implementation of the algorithm is discussed and simulation results confirm the efficiency of the proposed algorithm. Results from recent flight tests are also provided.

Vision-Based Tracking and Motion Estimation for Moving Targets Using Unmanned Air Vehicles

“…Another approach reported in [20] includes automatic camera placement that increases the feasible region, circumvents occlusions, and provides uninterrupted tracking. Alternative to pure vision or image processing techniques is a variety of optical flow algorithms [7,[21][22][23] addressing the task of 3-D motion reconstruction from the fast sampled 2-D image samples. The computation of optical flow (velocity field) involves several assumptions resulting in numerical issues of differentiation (ill-posed problem); however, the framework is initially designed to succeed in the presence of occlusions.…”

“…One solution [21] to this problem consists of employing multiple UAVs that can maintain an uninterrupted view of the target from different locations and angles. Another involves a swarm of micro UAVs deployed from a mother ship that can provide imagery of the hidden targets.…”

Optimization of Pesticide Spraying Tasks via Multi-UAVs Using Genetic Algorithm

“…However, for UAV task allocation problems, due to the constraints of the UAV's kinematic constraints, the distance between targets visited by UAVs is no longer Euclidean distance but rather Dubins path length. The Dubins path is a feasible trajectory of the minimum length over a bounded curvature trajectory at a constant rate [29], and it has been widely used in the field of UAV trajectory planning [5,[30][31][32]. In addition, for multi-UAV pesticide spraying assignment problems, due to the many possible points for UAVs to enter and exit the farmland, there are multiple Dubins paths between farmlands.…”

Market-Based Framework for Mobile Surveillance Systems

“…Second it considers how to coordinate the behavior of the sensors team in order to do the cooperative tasks efficiently. The past decade has witnessed a growing emphasis in research topics highlighting task allocation [20,[45][46][47][48]. Established techniques can be leveraged to help tackle task allocation aspects.…”