Articles (14)


24 June 2024

An Integer Programming Approach to Multi-Trip Routing of Delivery Drones at Load-Dependent Flight Speed

In recent years, there has been a growing interest in utilizing drones for parcel delivery among companies, aiming to address logistical challenges. However, effective optimization of delivery routes is essential. A theoretical framework termed the Flight Speed-aware Vehicle Routing Problem (FSVRP) has emerged to address the variability in drone flight speed based on payload weight. Several approximate methods have been proposed to solve the FSVRP. Our research endeavors to optimize parcel delivery efficiency and reduce delivery times by introducing a novel delivery problem. This problem accounts for multiple deliveries while considering the variability in flight speed due to diverse payloads. Through experimentation, we evaluate the efficacy of our proposed method compared to existing approaches. Specifically, we assess total flight distance and flight time. Our findings indicate that even in cases where the payload exceeds maximum capacity, all parcels can be delivered through multiple trips. Furthermore, employing a multi-trip FSVRP approach results in an average reduction of 10% in total flight time, even when payload capacities are not exceeded.

Mao Nishira
Hiroki Nishikawa
Xiangbo Kong
Hiroyuki Tomiyama*


12 June 2024

Optimized Real Time Single-Drone Path Planning for Harvesting Information from a Wireless Sensor Network

We consider a remote sensing system in which fixed sensors are placed in a region, and a single drone flies over the region to collect information from cluster heads. We assume that the drone has a fixed maximum range and that the energy consumption for information transmission from the cluster heads increases with distance according to a power law. Given these assumptions, we derive local optimum conditions for a drone path that either minimizes the total or maximum energy required by the cluster heads to transmit information to the drone. We show how a homotopy approach can produce a family of solutions for different drone path lengths so that a locally optimal solution can be found for any drone range. We implement the homotopy solution in Python and demonstrate the tradeoff between drone range and cluster head power consumption for several geometries. Execution time is sufficiently rapid for the computation to be performed in real time so that the drone path can be recalculated on the fly. The solution is shown to be globally optimal for sufficiently long drone path lengths. A proof of concept implementation in Python is available on GitHub. For future work, we indicate how the solution can be modified to accommodate moving sensors.

Ramkumar  Ganapathy
Christopher  Thron*


05 June 2024

An Architecture for Early Wildfire Detection and Spread Estimation Using Unmanned Aerial Vehicles, Base Stations, and Space Assets

This paper presents, an autonomous and scalable monitoring system for early detection and spread estimation of wildfires by leveraging low-cost UAVs, satellite data and ground sensors. An array of ground sensors, such as fixed towers equipped with infrared cameras and IoT sensors strategically placed in areas with a high probability of wildfire, will work in tandem with the space domain as well as the air domain to generate an accurate and comprehensive flow of information. This system-of-systems approach aims to take advantage of the key benefits across all systems while ensuring seamless cooperation. Having scalability and effectiveness in mind, the system is designed to work with low-cost COTS UAVs that leverage infrared and RGB sensors which will act as the primary situational awareness generator on demand. AI task allocation algorithms and swarming-oriented area coverage methods are at the heart of the system, effectively managing the aerial assets High-level mission planning takes place in the GCS, where information from all sensors is gathered and compiled into a user-understandable schema. In addition, the GCS issues warnings for events such as the detection of fire and hardware failures, live video feed and lower-level control of the swarm and IoT sensors when requested. By performing intelligent sensor fusion, this solution will offer unparalleled reaction times to wildfires while also being resilient and reconfigurable should any hardware failures arise by incorporating state of the art swarming capabilities.

Dimitrios Meimetis
Sofia Papaioannou
Paraskevi Katsoni
Vaios Lappas*


08 May 2024

Assessing Drone Return-to-Home Landing Accuracy in a Woodland Landscape

While aerial photography continues to play an integral role in forest management, its data acquisition can now be obtained through an unmanned aerial vehicle (UAV), commonly referred as a drone, instead of conventional manned aircraft. With its feasibility, a drone can be programed to take off, fly over an area following predefined paths and take images, then return to the home spot automatically. When flying over forests, it requires that there is an open space for a vertical takeoff drone to take off vertically and return safely. Hence, the automatic return-to-home feature on the drone is crucial when operating in a woodland landscape. In this project, we assessed the return-to-home landing accuracy based on a permanently marked launch pad nested in a wooded area on the campus of Stephen F. Austin State University in Nacogdoches, Texas. We compared four models of the DJI drone line, with each flown 30 missions over multiple days under different weather conditions. When each drone returned to the home launch spot and landed, the distance and direction from the launch spot to the landing position was measured. Results showed that both the Phantom 4 Advanced and the Spark had superior landing accuracy, whereas the Phantom 3 Advanced was the least accurate trailing behind the Phantom 4 Pro.

I-Kuai Hung*
Daniel Unger
Yanli Zhang
David Kulhavy


26 April 2024

Exact and Heuristic Approaches to Surveillance Routing with a Minimum Number of Drones

The rising cost and scarcity of human labor pose challenges in security patrolling tasks, such as facility security. Drones offer a promising solution to replace human patrols. This paper proposes two methods for finding the minimum number of drones required for efficient surveillance routing: an ILP-based method and a greedy method. We evaluate these methods through experiments, comparing the minimum number of required drones and algorithm runtime. The findings indicate that the ILP-based method consistently yields the same or a lower number of drones needed for surveillance compared to the greedy method, with a 73.3% success rate in achieving better results. However, the greedy method consistently finishes within one second, whereas the ILP-based method sometimes significantly increases when dealing with 14 more locations. As a case study, we apply the greedy method to identify the minimum drone surveillance route for the Osaka-Ibaraki Campus of Ritsumeikan University.

Kaito Mori*
Mao Nishira
Hiroki Nishikawa
Hiroyuki Tomiyama


19 March 2024

Designing a Quadcopter for Fire and Temperature Detection with an Infrared Camera and PIR Sensor

In agriculture, medicine, and engineering, sudden fire outbreaks are prevalent. During such events, the ensuing fire spread is extensive and unpredictable, necessitating crucial data for effective response and control. To address this need, the current initiative focuses on utilizing an Unmanned Aerial Vehicle (UAV) with an Infrared (IR) sensor. This sensor detects and analyses temperature variations, accompanied by additional camera footage capturing thermal images to pinpoint the locations of the incidents precisely. The UAV’s programming is executed using Arduino-Nano and mission planner software, interfacing with the Pixhawk flight controller operating in a guided mode for autonomous navigation. The UAV configuration includes a radio module interfacing with Arduino-Nano, a flight controller, and remote-control functionality. The flight duration is approximately 10–15 min, contingent upon flight dynamics and environmental temperature. Throughout its airborne operation, the UAV transmits live telemetry and log feeds to the connected computer, displaying critical parameters such as altitude, temperature, battery status, vertical speed, and distance from the operator. The Pixhawk flight controller is specifically programmed to govern the UAV’s behavior, issuing warnings to the pilot in case of low voltage, prompting a timely landing to avert potential crashes. In case of in-flight instability or a crash, the mission planner can trace the UAV’s location, facilitating efficient recovery and minimizing costs and component availability losses. This integrated approach enhances situational awareness and mitigation strategies, offering a comprehensive solution for managing fire incidents in diverse fields.

Guruprasad  Rathinakumar
Efstratios L.Ntantis *


26 January 2024

A Lightweight Visual Navigation and Control Approach to the 2022 RoboMaster Intelligent UAV Championship

In this paper, an autonomous system is developed for drone racing. On account of their vast consumption of computing resources, the methods for visual navigation commonly employed are discarded, such as visual-inertial odometry (VIO) or simultaneous localization and mapping (SLAM). A series of navigation algorithms for autonomous drone racing, which can operate without the aid of the information on the external position, are proposed: one for lightweight gate detection, achieving gates detection with a frequency of 60 Hz; one for direct collision detection, seeking the maximum passability in-depth images. Besides, a velocity planner is adopted to generate velocity commands according to the results from visual navigation, which are enabled to perform a guidance role when the drone is approaching and passing through gates, assisting it in avoiding obstacles and searching for temporarily invisible gates. The approach proposed above has been demonstrated to successfully help our drone passing-through complex environments with a maximum speed of 2.5 m/s and ranked first at the 2022 RoboMaster Intelligent UAV Championship.

Sijie Yang
Wenqi Song
Runxiao Liu
Quan Quan*


16 January 2024

A Position-based Hybrid Routing Protocol for Clustered Flying Ad Hoc Networks

Unmanned aerial vehicles (UAVs) have been used to establish flying ad hoc networks (FANETs) to support wireless communication in various scenarios, from disaster situations to wireless coverage extensions. However, the operation of FANETs faces mobility, wireless network variations and topology challenges. Conventional mobile ad hoc network and vehicular ad hoc network routing concepts have rarely been applied to FANETs, and even then they have produced unsatisfactory performance due to additional challenges not found in such networks. For instance, position-based routing protocols have been applied in FANET, but have failed to achieve adequate performance in large networks. Clustering solutions have also been used in large networks, but with a significant overhead in keeping track of the complete topology. Hence, to solve this problem, we propose a hybrid position-based segment-by-segment routing mechanism for clustered FANETs. This approach facilitates traffic engineering across multiple wireless clusters by combining position-based inter-cluster routing with a rank-based intra-cluster routing approach capable of balancing traffic loads between alternative cluster heads. Simulation results show that our solution achieves, on average, a lower power consumption of 72.5 J, a higher throughput of 275 Mbps and a much lower routing overhead of 17.5% when compared to other state-of-the-art end-to-end routing approaches.

Godwin  Asaamoning*
Paulo  Mendes


27 November 2023

Enhancing the Monitoring Protocols of Intermittent Flow Rivers with UAV-Based Optical Methods to Estimate the River Flow and Evaluate Their Environmental Status

Temporary streams are a key component of the hydrological cycle in arid and semi-arid regions, but their flow is highly variable and difficult to measure. In this paper, we present a novel approach that could be used to assess the flow of temporary streams this allowing to characterize their environmental status. Specifically, we apply the Image Velocimetry (IV) method to estimate surface velocity in temporary streams using Unmanned Aerial Vehicles (UAVs) equipped with optical sensors (IV-UAV method). The IV-UAV method enables the easy, safe and quick estimation of the velocity on the water’s surface. This method was applied in different temporary streams in Lesvos Island, Greece. The results obtained indicate that the IV-UAV can be implemented at low discharges, temporary streams and small streams. Specifically, the water depth ranged from 0.02 m to 0.28 m, while the channel width ranged from 0.6 m to 4.0 m. The estimated surface velocity ranged from 0.0 to 5.5 m/s; thus, the maximum water discharge was 0.60 m3/s for the largest monitored stream of the island. However, there were many occasions that measurements were unable due to various reasons such as dense vegetation or archaeological sites. Despite of this, the proposed methodology could be incorporated in optical protocols which are used to assess the environmental status of temporary streams of Mediterranean conditions. Finally, this would become a valuable tool for understanding the dynamics of these ecosystems and monitoring changes over time.

Paschalis Koutalakis*
Mairi-Danai Stamataki
Ourania Tzoraki


08 November 2023

Review on Drone-Assisted Air-Quality Monitoring Systems

Drone-aided systems have gained popularity in the last few decades due to their stability in various commercial sectors and military applications. The conventional ambient air quality monitoring stations (AAQMS) are immovable and big. This drawback has been significantly overcome by drone-aided low-cost sensor (LCS) modules. As a result, much research work, media information, and technical notes have been released on drone-aided air quality and ecological monitoring and mapping applications. This work is a sincere effort to provide a comprehensive and structured review of commercial drone applications for air quality and environmental monitoring. The collected scientific and non-scientific information was divided according to the different drone models, sensor types, and payload weights. The payload component is very critical in stablility of the multirotor drones. Most study projects installed inexpensive sensors on drones according to the avilibility of the space on drone frame. After reviewing of multiple environmental applications the common payload range was 0 gm to 4000 gm. The crucial elements are addressed, including their relation to meteorological factors, air isokinetics, propeller-induced downwash, sensor mounting location, ramifications etc. As a result, technical recommendations for AQ monitoring assisted by drones are addressed in the debate part. This work will help researchers and environmentalists choose sensor-specific payloads for drones and mounting locations. Also, it enables advanced methods of monitoring parameters that help policymakers to frame advanced protocols and sensor databases for the environment and ecology.

Piyush Kokate*
Anirban Middey
Shashikant  Sadistap
Gaurav Sarode
Anvesha Narayan