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 comple… Show more
“…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.…”
Section: Doi: 102514/133206mentioning
confidence: 99%
“…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.…”
“…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.…”
Section: Doi: 102514/133206mentioning
confidence: 99%
“…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.…”
“…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.…”
Task allocation is the key factor in the spraying pesticides process using unmanned aerial vehicles (UAVs), and maximizing the effects of pesticide spraying is the goal of optimizing UAV pesticide spraying. In this study, we first introduce each UAV's kinematic constraint and extend the Euclidean distance between fields to the Dubins path distance. We then analyze the two factors affecting the pesticide spraying effects, which are the type of pesticides and the temperature during the pesticide spraying. The time window of the pesticide spraying is dynamically generated according to the temperature and is introduced to the pesticide spraying efficacy function. Finally, according to the extensions, we propose a team orienteering problem with variable time windows and variable profits model. We propose the genetic algorithm to solve the above model and give the methods of encoding, crossover, and mutation in the algorithm. The experimental results show that this model and its solution method have clear advantages over the common manual allocation strategy and can provide the same results as those of the enumeration method in small-scale scenarios. In addition, the results also show that the algorithm parameter can affect the solution, and we provide the optimal parameters configuration for the algorithm.
“…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.…”
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