UBAT: On Jointly Optimizing UAV Trajectories and Placement of Battery Swap Stations

Unmanned aerial vehicles (UAVs) have been widely used in many applications. The limited flight time of UAVs, however, still remains as a major challenge. Although numerous approaches have been developed to recharge the battery of UAVs effectively, little is known about optimal methodologies to deploy charging stations. In this paper, we address the charging station deployment problem with an aim to find the optimal number and locations of charging stations such that the system performance is maximized. We show that the problem is NP-Hard and propose UBAT, a heuristic framework based on the ant colony optimization (ACO) to solve the problem. Additionally, a suite of algorithms are designed to enhance the execution time and the quality of the solutions for UBAT. Through extensive simulations, we demonstrate that UBAT effectively performs multi-objective optimization of generation of UAV trajectories and placement of charging stations that are within 8.3% and 7.3% of the true optimal solutions, respectively.Comment: Accepted for publication in ICRA, 202

Path planning and collision risk management strategy for multi-UAV systems in 3D environments

This article belongs to the Special Issue Smooth Motion Planning for Autonomous VehiclesMulti-UAV systems are attracting, especially in the last decade, the attention of researchers and companies of very different fields due to the great interest in developing systems capable of operating in a coordinated manner in complex scenarios and to cover and speed up applications that can be dangerous or tedious for people: search and rescue tasks, inspection of facilities, delivery of goods, surveillance, etc. Inspired by these needs, this work aims to design, implement and analyze a trajectory planning and collision avoidance strategy for multi-UAV systems in 3D environments. For this purpose, a study of the existing techniques for both problems is carried out and an innovative strategy based on Fast Marching Square¿for the planning phase¿and a simple priority-based speed control¿as the method for conflict resolution¿is proposed, together with prevention measures designed to try to limit and reduce the greatest number of conflicting situations that may occur between vehicles while they carry out their missions in a simulated 3D urban environment. The performance of the algorithm is evaluated successfully on the basis of certain conveniently chosen statistical measures that are collected throughout the simulation runs.This research was funded by the EUROPEAN COMMISSION: Innovation and Networks Executive Agency (INEA), through the European H2020 LABYRINTH project. Grant agreement H2020-MG-2019-TwoStages-861696

Exact and heuristic algorithms for multi-robot system routing, oriented to underwater monitoring. ​

The exploration of the underwater environment has always been a relevant field for science and technology, to enlarge our knowledge of this mainly unexplored environment. In this work, we apply a vehicle routing optimization method for underwater exploration and monitoring based on a fleet of small autonomous underwater vehicles (AUVs). We assume a coarse-grained map is already available from satellite measurements and the set of robots is used to get detailed information on sea bottom features. We provide exact and heuristic linear programming methods for finding both the optimal starting position and path planning for a fleet of drones. To obtain a realistic model useful in real applications, we enhance our formulation by imposing connectivity constraints among the AUVs. Lastly, we present a use case application for coral reef monitoring with real data taken by Abu Dhabi environmental authorities.The exploration of the underwater environment has always been a relevant field for science and technology, to enlarge our knowledge of this mainly unexplored environment. In this work, we apply a vehicle routing optimization method for underwater exploration and monitoring based on a fleet of small autonomous underwater vehicles (AUVs). We assume a coarse-grained map is already available from satellite measurements and the set of robots is used to get detailed information on sea bottom features. We provide exact and heuristic linear programming methods for finding both the optimal starting position and path planning for a fleet of drones. To obtain a realistic model useful in real applications, we enhance our formulation by imposing connectivity constraints among the AUVs. Lastly, we present a use case application for coral reef monitoring with real data taken by Abu Dhabi environmental authorities

SuSy-EnGaD: Surveillance System Enhanced by Games of Drones

In this article, we propose SuSy-EnGaD, a surveillance system enhanced by games of drones. We propose three different approaches to optimise a swarm of UAVs for improving intruder detection, two of them featuring a multi-objective optimisation approach, while the third approach relates to the evolutionary game theory where three different strategies based on games are proposed. We test our system on four different case studies, analyse the results presented as Pareto fronts in terms of flying time and area coverage, and compare them with the single-objective optimisation results from games. Finally, an analysis of the UAVs trajectories is performed to help understand the results achieved

Study of new technological implications to improve food productivity and security in Ghana : case insights into the use of drones in cocoa farming

Since the early 1980’s, in developed countries such as Japan and the United States of America, several technological applications have been used experimentally to boost food production and enhance farming practices, especially in areas which are not geographically accessible for traditional farming practices and machineries.One such technology which has been extensively experimented with and deployed is the Unmanned Aerial Vehicle (UAV), which is an example of technological expertise pioneered by the military. Their growing adaptation in precision agriculture means that UAV have been used on farms in developed countries for crops grown on both small- and large land acreage for the purposes of identifying nutrient deficiencies, diseases, water and soil status, weeds, damage, and plant diagnostics.The study focuses on the adaptation and implementation of UAV in Ghana’s cocoa farming and the position of stakeholders in terms of their acceptance, as the country is currently the world’s second largest producer and exporter of cocoa. The study applies Disruptive Innovation theory and stakeholder theory as a joint conceptual framework by which to examine how new and long-established farms create, sustain, and continuously introduce creative and novel technology in order to maximise food production while assessing stakeholders’ attitudes and roles in the implementation of innovation.Conducted in Nkawie in the Ashanti region of Ghana, the study adopts a qualitative approach, using semi-structured interviews to elicit and collate the views of stakeholders on the implementation of UAV in cocoa farming in Ghana, ultimately analysing the resulting by use of NVivo software. The findings show that traditional practices and superstitious beliefs, lack of credit facilities can impede the acceptance of new innovation.The study identifies a comprehensive pool of stakeholders in the supply chain whose input significantly influences the implementation of UAV. Other key stakeholders maintained that limited support for local drone innovator community, access to funding, and corrupt practices hinder the implementation of this technology, although general awareness of its benefit to cocoa farming cannot be disputed. Despite the difficult conditions that arose during data collection due to COVID restrictions in the study area, 36 participant agreed to participate in the study through interviews. This study makes a specific contribution to the body of literature and policy framework on the drivers and barriers of UAV adoption and implementation in emerging economies such as Ghana in the cocoa farming industr