Drone Systems and Applications

This paper presents and assesses the feasibility and potential of a novel concept: the operation of multiple Unmanned Aerial Vehicles (UAVs) commanded and supported by a manned “Tender” air vehicle carrying a pilot and flight manager(s). The “Tender” is equipped to flexibly and economically monitor and manage multiple diverse UAVs over otherwise inaccessible terrain through wireless communication. The proposed architecture enables operations and analysis supported by the means to detect, assess, and accommodate change and hazards on the spot with effective human observation and coordination. Further, this paper seeks to find the optimal trajectories for UAVs to collect data from sensors in a predefined continuous space. We formulate the path-planning problem for a cooperative, and a diverse swarm of UAVs tasked with optimizing multiple objectives simultaneously with the goal of maximizing accumulated data within a given flight time within cloud data processing constraints as well as minimizing the probable imposed risk during UAVs mission. The risk assessment model determines risk indicators using an integrated Specific Operation Risk Assessment—Bayesian belief network approach, while its resultant analysis is weighted through the analytic hierarchy process ranking model. To this end, as the problem is formulated as a convex optimization model, and we propose a low complexity multi-objective reinforcement learning (MORL) algorithm with a provable performance guarantee to solve the problem efficiently. We show that the MORL architecture can be successfully trained and allows each UAV to map each observation of the network state to an action to make optimal movement decisions. This proposed network architecture enables the UAVs to balance multiple objectives. Estimated MSE measures show that the algorithm produced decreasing errors in the learning process with increasing epoch number.

Richard C. Millar

Leila Hashemi

Armin Mahmoodi

Robert Walter Meyer

Jeremy Laliberte

Integrating unmanned and manned UAVs data network based on combined Bayesian belief network and multi-objective reinforcement learning algorithm

基于贝叶斯信念网络与多目标强化学习算法的无人与有人无人机数据网络集成

With the growing availability of remotely sensed aerial data, non-invasive archaeological prospection and characterization have become increasingly viable. While such approaches are comparatively well-developed at sites with prominent remnant structures, their utility is less clear when surface and subsurface features are only subtly indicated. This case study addresses the utility of aerial remote sensing using two western Canadian fur trade posts with only modest surface evidence. We consider public domain imagery at diverse resolutions and compare it with output from Unmanned Aerial Vehicles, and also the integration of such data with archival imagery to aid in interpretation of archaeological features.

Scott Hamilton

Nick Kuncewicz

Non-invasive archaeological site characterization: Case studies from Fort Ellice 1 and 2, Canada.

非侵入性考古遗址特征分析：以加拿大埃利斯堡1号和2号遗址为例。

Drones may be valuable in polar research because they can minimize researcher activity and overcome logistical, financial, and safety obstacles associated with wildlife research in polar regions. Because polar species may be particularly sensitive to disturbance and some research suggests behavioral responses to drones are species-specific, there is a need for focal species-specific disturbance assessments. We evaluated behavioral responses of nesting Common Eiders (Somateria mollissima (Linnaeus, 1758), n = 19 incubating females) to first, second, or in a few cases third exposure of fixed-wing drone surveys using nest cameras. We found no effect of drone flights (F [1,23] = 0, P = 1.0) or previous exposures (F [1,23] = 0.75, P = 0.397) on the probability of a daily recess event (bird leaves nests). Drone flights did not impact recess length (F [1,25] = 1.34, P = 0.26); however, Common Eiders with prior drone exposure took longer recess events (F [1,25] = 5.27, P = 0.03). We did not observe any overhead vigilance behaviors common in other species while the drone was in the air, which may reflect Common Eiders’ anti-predator strategies of reducing activity at nests in response to aerial predators. Surveying nesting Common Eider colonies with a fixed-wing drone did not result in biologically meaningful behavioral changes, providing a potential tool for research and monitoring this polar nesting species.

Susan N. Ellis-Felege

Tanner Stechmann

Samuel Hervey

Christopher J. Felege

Robert F. Rockwell

Andrew F. Barnas

Nesting Common Eiders (<i>Somateria mollissima</i>) show little behavioral response to fixed-wing drone surveys

巢居普通海鸭（<i>Somateria mollissima</i>）对固定翼无人机调查表现出较小的行为反应

Effective management of animal populations requires knowledge of life history parameters and estimates of population abundance. One method commonly used to estimate abundance is capture–recapture analyses of photographs. Small, relatively inexpensive, rotary-wing drones have become an effective platform for obtaining high-quality aerial photographs of whales. To conduct capture–recapture analyses the animal needs to be defined as marked or unmarked and the photographs must be of high quality. While a system for scoring quality and markedness has previously been developed for bowhead whales (Balaena mysticetus Linnaeus, 1758) ( Rugh et al. 1998 . Rep. int. Whal. Commn. 48: 501–512), a revised scoring system was needed to incorporate increased information in photographs taken by drones. We present a revised scoring system that enlarges two of the previously defined areas of the whale examined for markings and incorporates smaller markings into the definition of marked whales. We scored 30 whales using the previous criteria and the revised criteria developed in this paper. More whales were identified as marked (23%) and mark scores were higher for 30% of the zones scored using the new system. Increasing the number of marked whales during capture–recapture studies increases the precision of estimated parameters and permits us to make those estimates with smaller samples of photographs.

William R. Koski

Brent G. Young

A new scoring system for use in capture–recapture studies for bowhead whales photographed with drones

用于无人机拍摄的弓头鲸捕获-重捕研究的新评分系统

A quadcopter manipulator system is an aerial robot consisting of a quadcopter with a robotic arm attached to it. The system has coupled nonlinear dynamics with uncertain time-varying parameters. The work in this paper focuses on designing an adaptive nonlinear controller to facilitate the uncertain system’s trajectory tracking and stability. The novelty of the proposed work is the design and implementation of an adaptive feedback linearization controller, called adaptive augmented torque (AAT) control, for the aerial robot. The control law is based on a feedback linearization controller with model reference adaptive controller and a tracking error-based augmented term. Using the input-to-state stability concept, a bound on the parameter estimation error is also developed. In the presented methodology, the controller uses estimated values of system parameters obtained from the adaptive mechanism and the tracking error to compute the control input using the AAT control law. An adaptive law for estimating unknown parameters is obtained using the strictly positive real-Lyapunov method. The asymptotic stability of the closed-loop system is analyzed via the Lyapunov theory. Simulations implemented in MATLAB and ROS/Gazebo and preliminary hardware experiments are presented to validate the theoretical results and to corroborate the performance of the AAT control law.

Vidya Sumathy

Debasish Ghose

Adaptive augmented torque control of a quadcopter with an aerial manipulator

四旋翼无人机搭载空中机械手的自适应增强扭矩控制

Advanced Air Mobility (AAM) is an emerging field that envisions highly automated, high-tempo, passenger-carrying aircraft operating in urban environments. Numerous stakeholders have emerged in this space, each proposing unique concepts of operation (CONOPS). While this technology will enable a revolutionary leap in modern transportation, many challenges remain unaddressed. Discrepancies exist between envisioned AAM operations, current technology, and outdated federal regulations. This has led to an unclear vision within the industry of the current maturity level of technology and the path of development needed to achieve proposed CONOPS. We seek to fill this gap by integrating multiple proposed conceptual systems into a single, unified path forward for the field. The literature on AAM covers a diverse array of interconnected themes, each containing a multitude of considerations that require extensive exploration and understanding. In the present work, a literature integration was conducted to collate the numerous proposed concepts and envisioned works that exist within the AAM literature. With this information, a comprehensive AAM taxonomy was created to represent this integration of concepts and rectify the inconsistencies within industry CONOPS. This taxonomy will assist future stakeholders in navigating this intricate field while contributing to the safe and efficient development and deployment of AAM.

Ryan A Lange

Stephen Rice

Ryan J. Wallace

Scott R. Winter

Mattie N. Vasquez

Stephen Woods

Creation of a System Taxonomy for Advanced Air Mobility Operations

先进空中交通运营系统分类的创建

In this paper, we present a novel formation control approach in the framework of Event-Triggered (ET) control to provide a solution to the surveillance problem. To do this, we identify two main challenges which are the switching topology of the drones and the limited bandwidth of the communication network, which are also valid in formation applications. To provide a solution to switching topologies, we propose a networked continuous controller that is robust in the presence of connection switching between drones and the target. Then, we propose a networked controller with ET communication in some aperiodic instants which reduces the required bandwidth and load within the communication network. We guarantee the stability of the developed ET controller and prove that the Zeno behavior cannot occur. To validate the method, we present realistic 3D simulation results conducted in the Simulink environment of Matlab® for different scenarios. The results of the study show the effectiveness of the proposed controller, especially for limited bandwidth channels as the ETC scheme has decreased the load within the communication network while resulting in a robust and efficient formation performance. We also considered moving target scenarios with missing possibilities to validate the robustness of the proposed method.

Farzad Hashemzadeh

Tufan Kumbasar

Swarm of Drones for Surveillance Monitoring of a Grounded Target: An event-triggered approach

无人机群对地面目标的监视监测：一种事件触发的方法

In this paper, the authors’ previous work regarding a conceptual drone-assisted Autonomous Pollination System (APS) is extended with regards to path planning and flight control. The APS Path Planning module is extended to optimize the path for missions requiring three-dimensional (3D) path planning, such as the pollination of almond trees. A new method of simplifying the 3D path planning problem by selecting cells or groups of flowers to visit is shown in this paper. This method is numerically demonstrated based on a simulated almond tree. The Flight Control module is extended to incorporate drag into a novel convex-optimization-based flight controller and a new method of collision avoidance called Control Sequence Stitching (CSS). A linear drag model is integrated into the flight control formulation, which is validated through a simulated test flight. The concept of CSS is developed and explained as a method to generate seamless flight trajectories while still reaping the benefits of convex optimization. This method can be used to generate collision-free trajectories and control commands rapidly for potential real-world APS missions.

Chapel R Rice

Hao Gan

Zhenbo Wang

Three-Dimensional Path Planning and Collision-Free Flight Control for Drone-Assisted Autonomous Pollination Systems

无人机辅助自主授粉系统的三维路径规划与无碰撞飞行控制

For flapping-wing micro aerial vehicles, the common approach to converting the rotational motion of a DC motor to the reciprocal flapping motion is using a slider-crank mechanism. However, frictional losses in sliders and rotational joints can hinder the performance of such a system. An alternative is a direct drive system where the wings are directly connected to a DC motor which has been driven by an AC signal. These two approaches are compared in this paper, to evaluate their performances and assess which one provides a better solution for flapping wing micro drones. The electromechanical model of the two systems is used in this paper to compare their performances. System parameters for both types of drones were derived through a multi-variable optimisation process using the same DC motor. The comparisons are made in terms of input power requirement, aerodynamic power, system efficiency and lift. The direct drive model can generate about 16 % higher average lift at 5 V with 50 % lower input electrical power. It has 29 % larger aerodynamic power and the system efficiency is 16.0 % higher than that of the slider-crank model.

MOONSOO PARK

Ali Abolfathi

Direct drive or slider-crank? Comparing motor-actuated flapping-wing micro aerial vehicles

直接驱动还是曲柄滑块？比较电动扑翼微型飞行器

Abbreviation	Drone Syst. Appl.
Journal Impact	1.81
Quartiles(Global)	REMOTE SENSING(Q3)

ISSN	2564-4939
h-index	28

Publication Information	Publisher: Canadian Science Publishing，Publishing cycle: ，Journal Type: journal，Open Access Journals: Yes
Basic data	Year of publication: 2022，Proportion of original research papers: 91.30%，Self Citation Rate:， Gold OA Rate: 96.15%
Journal Fees	$1000Details
Average review cycle	31 weeks

Drone Systems and Applications

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Integrating unmanned and manned UAVs data network based on combined Bayesian belief network and multi-objective reinforcement learning algorithm

Non-invasive archaeological site characterization: Case studies from Fort Ellice 1 and 2, Canada.

Nesting Common Eiders (Somateria mollissima) show little behavioral response to fixed-wing drone surveys

A new scoring system for use in capture–recapture studies for bowhead whales photographed with drones

Adaptive augmented torque control of a quadcopter with an aerial manipulator

Non-invasive archaeological site characterization: Case studies from Fort Ellice 1 and 2, Canada.

Creation of a System Taxonomy for Advanced Air Mobility Operations

Swarm of Drones for Surveillance Monitoring of a Grounded Target: An event-triggered approach

Three-Dimensional Path Planning and Collision-Free Flight Control for Drone-Assisted Autonomous Pollination Systems

Direct drive or slider-crank? Comparing motor-actuated flapping-wing micro aerial vehicles