Routing and Scheduling of Unmanned Aerial Vehicles Subject to Cyclic Production Flow Constraints

Bocewicz, Grzegorz; Nielsen, Peter; Banaszak, Zbigniew; Thibbotuwawa, Amila

doi:10.1007/978-3-319-99608-0_9

Cited by 22 publications

(12 citation statements)

References 12 publications

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“…The proposed declarative solution approach enables one to state a decision support-driven reference model aimed at the analysis of the relationships between the structure of a given UAV-driven supply network and its potential behavior, resulting in a sequence of sub-missions following required deliveries. From this perspective, the results of this study fall within the scope of the research presented in the papers [19][20][21][22][23][24].…”

Section: Introductionsupporting

confidence: 60%

A Solution Approach for UAV Fleet Mission Planning in Changing Weather Conditions

et al. 2019

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With a rising demand for utilizing unmanned aerial vehicles (UAVs) to deliver materials in outdoor environments, particular attention must be given to all the different aspects influencing the deployment of UAVs for such purposes. These aspects include the characteristics of the UAV fleet (e.g. size of fleet, UAV specifications and capabilities), the energy consumption (highly affected by weather conditions and payload) and the characteristics of the network and customer locations. All these aspects must be taken into account when aiming to achieve deliveries to customers in a safe and timely manner. However, at present, there is a lack of decision support tools and methods for mission planners that consider all these influencing aspects together. To bridge this gap, this paper presents a decomposed solution approach, which provides decision support for UAVs’ fleet mission planning. The proposed approach assists flight mission planners in aerospace companies to select and evaluate different mission scenarios, for which flight-mission plans are obtained for a given fleet of UAVs, while guaranteeing delivery according to customer requirements in a given time horizon. Mission plans are analyzed from multiple perspectives including different weather conditions (wind speed and direction), payload capacities of UAVs, energy capacities of UAVs, fleet sizes, the number of customers visited by a UAV on a mission and delivery performance. The proposed decision support-driven declarative model supports the selection of the UAV mission planning scenarios subject to variations on all these configurations of the UAV system and variations in the weather conditions. The computer simulation based experimental results, provides evidence of the applicability and relevance of the proposed method. This ultimately contributes as a prototype of a decision support system of UAVs fleet-mission planning, able to determine whether is it possible to find a flight-mission plan for a given fleet of UAVs guaranteeing customer satisfaction under the given conditions. The mission plans are created in such a manner that they are suitable to be sent to Air Traffic Control for flight approval.

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Section: Introductionsupporting

confidence: 60%

A Solution Approach for UAV Fleet Mission Planning in Changing Weather Conditions

et al. 2019

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“…From the literature, one can identify that there are several aspects that necessitate treating the problem differently from traditional transportation problems. UAVs are limited by their loading capacity as well as their flight duration, which is linked to the energy capacity of the UAV [2,3,14,28]. These constraints are typically addressed in transportation problems.…”

Section: Literature Reviewmentioning

confidence: 99%

“…However, UAVs have the additional complexity that the flight duration heavily depends on the payload carried which requires these characteristics to be taken into consideration in UAV mission planning [29,30]. Weather is critical for energy consumption as it affects the travel speed of the UAV (and thus total energy consumed), and the ambient temperature affects the energy capacity [2,3,28] of batteries used in UAVs. Cold temperatures may adversely affect battery performance until the batteries warm up [2,15].…”

Section: Literature Reviewmentioning

confidence: 99%

UAV Mission Planning Resistant to Weather Uncertainty

Thibbotuwawa

Bocewicz

Radzki

et al. 2020

Sensors

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Fleet mission planning for Unmanned Aerial Vehicles (UAVs) is the process of creating flight plans for a specific set of objectives and typically over a time period. Due to the increasing focus on the usage of large UAVs, a key challenge is to conduct mission planning addressing changing weather conditions, collision avoidance, and energy constraints specific to these types of UAVs. This paper presents a declarative approach for solving the complex mission planning resistant to weather uncertainty. The approach has been tested on several examples, analyzing how customer satisfaction is influenced by different values of the mission parameters, such as the fleet size, travel distance, wind direction, and wind speed. Computational experiments show the results that allow assessing alternative strategies of UAV mission planning.

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“…Technological advances in the area of UAV have been impressive, and this leads to an increased degree of automation of these systems [24]. In production systems, the majority of research has been focused on automated guided vehicles (AGVs) [25], mobile robot routing [26][27][28][29][30][31][32][33][34], or six degrees of freedom aerial robots [35], which are UAVs.…”

Section: Uav Routing With An Emphasis On the Problem Type Transportat...mentioning

confidence: 99%

“…It is observed that certain modes of transportation are fully automated and certain modes are semi-automated [56,58]. Automated guided transport (AGT) systems and AGVs fall under the fully automated modes of transportation and have been subjected to intense study in literature [25,27,[59][60][61][62]. In maritime transport, automated vessel routing has been introduced and unmanned vessels will be the future of maritime transportation [63].…”

Section: Degree Of Automationmentioning

confidence: 99%

Unmanned Aerial Vehicle Routing Problems: A Literature Review

et al. 2020

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Unmanned aerial vehicle (UAV) routing is transitioning from an emerging topic to a growing research area as the 3D flexible utilization of airspace, promogulated by UAVs, is a potential game changer in solving the urban air mobility challenge by allowing to reshape transportation and logistics in the future. This has revealed a need to classify different types of research and examine the general characteristics of the research area. This research aims to assist in identifying the main topics and emerging research streams and provides a published overview of the current state and contributions to the area of the UAV routing problem (UAVRP) and a general categorization of the vehicle routing problem (VRP) followed by a UAVRP classification with a graphical taxonomy based on the analysis of UAVRP current status. To achieve this, an analysis of the existing research contributions promulgated in this domain is conducted. This analysis is used to identify the current state of UAVRP and the gaps related to the UAVs’ flight dynamics and weather conditions, which significantly influence the fuel consumption of the UAV when modeling the UAVRP.

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Routing and Scheduling of Unmanned Aerial Vehicles Subject to Cyclic Production Flow Constraints

Cited by 22 publications

References 12 publications

A Solution Approach for UAV Fleet Mission Planning in Changing Weather Conditions

A Solution Approach for UAV Fleet Mission Planning in Changing Weather Conditions

UAV Mission Planning Resistant to Weather Uncertainty

Unmanned Aerial Vehicle Routing Problems: A Literature Review

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