MCO Plan: Efficient Coverage Mission for Multiple Micro Aerial Vehicles Modeled as Agents

Campo, Liseth Viviana; Ledezma, Agapito; Corrales, Juan Carlos

doi:10.3390/drones6070181

Cited by 3 publications

(2 citation statements)

References 40 publications

(41 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…OMNET++ [45] Task decomposition and task correlation of UAV swarm OMNET++ [46] Multiple UAVs collaborating for improved field phenotyping. Gazebo [47] Resource balancing for MAV (Mobile Aerial Vehicle). Gazebo [48] Development of a PSO-based threat avoidance and reconnaissance FANET.…”

Section: Reference Year Published Study Descriptionmentioning

confidence: 99%

Designing UAV Swarm Experiments: A Simulator Selection and Experiment Design Process

Phadke,

Medrano,

Sekharan

et al. 2023

Sensors

View full text Add to dashboard Cite

The rapid advancement and increasing number of applications of Unmanned Aerial Vehicle (UAV) swarm systems have garnered significant attention in recent years. These systems offer a multitude of uses and demonstrate great potential in diverse fields, ranging from surveillance and reconnaissance to search and rescue operations. However, the deployment of UAV swarms in dynamic environments necessitates the development of robust experimental designs to ensure their reliability and effectiveness. This study describes the crucial requirement for comprehensive experimental design of UAV swarm systems before their deployment in real-world scenarios. To achieve this, we begin with a concise review of existing simulation platforms, assessing their suitability for various specific needs. Through this evaluation, we identify the most appropriate tools to facilitate one’s research objectives. Subsequently, we present an experimental design process tailored for validating the resilience and performance of UAV swarm systems for accomplishing the desired objectives. Furthermore, we explore strategies to simulate various scenarios and challenges that the swarm may encounter in dynamic environments, ensuring comprehensive testing and analysis. Complex multimodal experiments may require system designs that may not be completely satisfied by a single simulation platform; thus, interoperability between simulation platforms is also examined. Overall, this paper serves as a comprehensive guide for designing swarm experiments, enabling the advancement and optimization of UAV swarm systems through validation in simulated controlled environments.

show abstract

Section: Reference Year Published Study Descriptionmentioning

confidence: 99%

Designing UAV Swarm Experiments: A Simulator Selection and Experiment Design Process

Phadke,

Medrano,

Sekharan

et al. 2023

Sensors

View full text Add to dashboard Cite

show abstract

“…According to Hassanalian and Abdelkefi [5], the size of MAVs is less than 500 mm and the maximum takeoff mass is approximately 200 g, so that they have a low aspect ratio (LAR) and low wing loading (W/S). Their missions have a range (flight distance) close to 15 km and an endurance (flying time) of around 30 min [6][7][8]. The demand for MAVs requires control, communication and navigation and a compact and light weight propulsion system with high aerodynamic efficiency (measured as the ratio between the lift and drag coefficients as E = C L C D ) to fulfill the endurance and range capabilities.…”

Section: Introductionmentioning

confidence: 99%

Numerical Analysis of Bioinspired Tails in a Fixed-Wing Micro Air Vehicle

Barroso Barderas,

Bardera Mora,

Rodriguez-Sevillano

et al. 2023

Aerospace

View full text Add to dashboard Cite

Bird tails play a key role in aerodynamics and flight stability. They produce extra lift for takeoff and landing maneuvers, enhance wing functions and maintain stability during flight (keeping the bird from yawing, rolling and pitching, or otherwise losing control). This paper investigates the use of bioinspired horizontal stabilizers for Micro Air Vehicles (MAVs) involving a Zimmerman wing-body geometry. A selection of five tail shapes of the main types existing in nature is presented, and a parametric analysis is conducted looking into the influence of the most relevant tail geometric parameters to increase the longitudinal static stability of the vehicle. Based on the parametric study, a smaller subset of candidate tail designs are shortlisted to perform a detailed aerodynamic analysis. Then, steady RANS CFD simulations are conducted for a higher-fidelity study of these candidate tail designs to obtain an optimum of each tail type. The criterion for selection of the optimum tail configuration is the maximum aerodynamic efficiency, CLCD , as well as a high longitudinal static stability. The squared-fan tail provides the highest aerodynamic efficiency while maintaining a high longitudinal stability of the vehicle. In conclusion, this paper provides an innovative study of improving longitudinal stability and aerodynamics through the implementation of bioinspired horizontal stabilizers in vehicles with these characteristics.

show abstract

UAV4PE: An Open-Source Framework to Plan UAV Autonomous Missions for Planetary Exploration

Galvez-Serna

Vanegas

Brar

et al. 2022

Drones

View full text Add to dashboard Cite

Autonomous Unmanned Aerial Vehicles (UAV) for planetary exploration missions require increased onboard mission-planning and decision-making capabilities to access full operational potential in remote environments (e.g., Antarctica, Mars or Titan). However, the uncertainty introduced by the environment and the limitation of available sensors has presented challenges for planning such missions. Partially Observable Markov Decision Processes (POMDPs) are commonly used to enable decision-making and mission-planning processes that account for environmental, perceptional (extrinsic) and actuation (intrinsics) uncertainty. Here, we propose the UAV4PE framework, a testing framework for autonomous UAV missions using POMDP formulations. This framework integrates modular components for simulation, emulation, UAV guidance, navigation and mission planning. State-of-the-art tools such as python, C++, ROS, PX4 and JuliaPOMDP are employed by the framework, and we used python data-science libraries for the analysis of the experimental results. The source code and the experiment data are included in the UAV4PE framework. The POMDP formulation proposed here was able to plan and command a UAV-based planetary exploration mission in simulation, emulation and real-world experiments. The experiments evaluated key indicators such as the mission success rate, the surface area explored and the number of commands (actions) executed. We also discuss future work aimed at improving the UAV4PE framework, and the autonomous UAV mission planning formulation for planetary exploration.

show abstract

MCO Plan: Efficient Coverage Mission for Multiple Micro Aerial Vehicles Modeled as Agents

Cited by 3 publications

References 40 publications

Designing UAV Swarm Experiments: A Simulator Selection and Experiment Design Process

Designing UAV Swarm Experiments: A Simulator Selection and Experiment Design Process

Numerical Analysis of Bioinspired Tails in a Fixed-Wing Micro Air Vehicle

UAV4PE: An Open-Source Framework to Plan UAV Autonomous Missions for Planetary Exploration

Contact Info

Product

Resources

About