Monitoring Moving Objects Using Aerial Mobile Sensors

Haugen, Joakim; Imsland, Lars

doi:10.1109/tcst.2015.2454432

Cited by 23 publications

(24 citation statements)

References 28 publications

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“…In some articles, drones not only have to locate the object, but also estimate its motion . For example, Haugen and Imsland and Albert et al set up a control framework to estimate parameters of motion of several objects with drones equipped with imperfect sensors. The application is motivated by detection of icebergs and assessment of their direction of movement, position, and velocity, as well as estimation of ice concentration in the sea.…”

Section: Planning Drone Operationsmentioning

confidence: 99%

Optimization approaches for civil applications of unmanned aerial vehicles (UAVs) or aerial drones: A survey

et al. 2018

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Unmanned aerial vehicles (UAVs), or aerial drones, are an emerging technology with significant market potential. UAVs may lead to substantial cost savings in, for instance, monitoring of difficult‐to‐access infrastructure, spraying fields and performing surveillance in precision agriculture, as well as in deliveries of packages. In some applications, like disaster management, transport of medical supplies, or environmental monitoring, aerial drones may even help save lives. In this article, we provide a literature survey on optimization approaches to civil applications of UAVs. Our goal is to provide a fast point of entry into the topic for interested researchers and operations planning specialists. We describe the most promising aerial drone applications and outline characteristics of aerial drones relevant to operations planning. In this review of more than 200 articles, we provide insights into widespread and emerging modeling approaches. We conclude by suggesting promising directions for future research.

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Section: Planning Drone Operationsmentioning

confidence: 99%

Optimization approaches for civil applications of unmanned aerial vehicles (UAVs) or aerial drones: A survey

et al. 2018

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“…The results in the following capture a run where this problem did not occur. Another run is illustrated in Haugen and Imsland (2014b). As can be seen in Figure 9, the planned paths were within the constraints of the vehicle model.…”

Section: Resultsmentioning

confidence: 99%

“…In this manuscript, we briefly discuss the following ice observation sub-tasks: target tracking, related to Mission 1, and dynamic coverage control, related to Mission 2. We provide an overview of common components that have been used to solve the mentioned sub-tasks in Haugen and Imsland (2014b) and Haugen and Imsland (2014a), respectively. We will finally display results from a hybrid field experiment of the target tracking task, which was first reported in Haugen and Imsland (2013b).…”

Section: Remotely Piloted Aircraft Systems In Cold Regionsmentioning

confidence: 99%

“…Many problems can be cast as a target tracking problem, so the literature is rich on various approaches, see Haugen and Imsland (2014b) and references therein. Haugen and Imsland (2014b) classify contributions in literature as "n m to n o " tracking, where n m is the number of sensors and n o is the number of objects. The above defined problem is a multi-target tracking objective, where the number of mobile sensor agents are possibly more than one.…”

Section: Target Trackingmentioning

confidence: 99%

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Autonomous Aerial Ice Observation for Ice Defense

Haugen¹,

Imsland²

2014

MIC

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One of the tasks in ice defense is to gather information about the surrounding ice environment using various sensor platforms. In this manuscript we identify two monitoring tasks known in literature, namely dynamic coverage and target tracking, and motivate how these tasks are relevant in ice defense using remotely piloted aircraft systems (RPASs). An optimization-based path planning concept is outlined for solving these tasks. A path planner for the target tracking problem is elaborated in more detail and a hybrid experiment, which consists of both a real fixed-wing aircraft and simulated objects, is included to show the applicability of the proposed framework.

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“…However, it did not take into account time constraints, so the problem was treated as a path following problem. [9] also shows a solution to track moving objects, but it optimizes the path according to the waypoints sequence, which has much more computational cost than the solution presented in this paper, where only the turn rate is controlled. In [10], a MPC algorithm running in a ground station is used to 1 ardupilot.org 2 mavlink.org 3 jsbsim.org 4 lsts.fe.up.pt/toolchain/dune 5 lsts.fe.up.pt/toolchain/imc control the UAV turning radius and the camera's gimbal to track objects in the sea.…”

Section: Introductionmentioning

confidence: 99%

Autonomous UAV surveillance of a ship's path with MPC for maritime situational awareness

Andrade

Storvold

Johansen

2017

2017 International Conference on Unmanned Aircraft Systems (ICUAS)

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Abstract-Maritime Situational Awareness is crucial in maritime operations to identify threats and to deal with them as soon as possible. These threats can be pirates in shipping operations, icebergs when sailing in the northern sea routes, or even unknown vessels or objects that might be on the ship's path. A solution to identify these threats is the use of UAV's to overfly the ship's planned path. This solution is described in this paper, using an autonomous fixed wing UAV. Based on the provided ship's planned path, the UAV should autonomously map the area close to the ship track. To do that, an optimization problem is solved using Model Predictive Control, where the turn rate for the next time period is optimized. Based on the turn rate, the future path of the UAV is calculated and the waypoints are sent to the autopilot. This application is thoroughly tested using a Software In Loop environment, where an aircraft model is used with the autopilot's simulation. The results show that surveillance performance is improved if the UAV has information about the ship's velocity in addition to position.

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Monitoring Moving Objects Using Aerial Mobile Sensors

Cited by 23 publications

References 28 publications

Optimization approaches for civil applications of unmanned aerial vehicles (UAVs) or aerial drones: A survey

Optimization approaches for civil applications of unmanned aerial vehicles (UAVs) or aerial drones: A survey

Autonomous Aerial Ice Observation for Ice Defense

Autonomous UAV surveillance of a ship's path with MPC for maritime situational awareness

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