A Full Distributed Multipurpose Autonomous Flight System Using 3D Position Tracking and ROS

Gargioni, Gustavo; Peterson, Marco; Persons, J. B.; Schroeder, Kevin; Black, Jonathan

doi:10.1109/icuas.2019.8798163

Cited by 12 publications

(6 citation statements)

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“…The results in [ 13 ] showed that accuracy depends on the implementation and methodology used. In particular, the technologies, which were applied in the development of autonomous vehicles, are global positioning systems by vision such as VICON [ 7 , 8 ], or Optitrack [ 14 , 15 ], Virtual Reality (VR) systems [ 16 , 17 ] and RF technology [ 18 , 19 , 20 ]. Meanwhile, the use of Ultra-Wide Band (UWB), part of the RF technologies, attracted interest during the last years [ 21 ], because with this technology it is also possible to obtain a good performance in terms of accuracy [ 22 ].…”

Section: Background and Related Workmentioning

confidence: 99%

Sensor Information Sharing Using a Producer-Consumer Algorithm on Small Vehicles

Vazquez-Lopez

Lozada

Sandoval-Gutierrez

et al. 2021

Sensors

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There are several tools, frameworks, and algorithms to solve information sharing from multiple tasks and robots. Some applications such as ROS, Kafka, and MAVLink cover most problems when using operating systems. However, they cannot be used for particular problems that demand optimization of resources. Therefore, the objective was to design a solution to fit the resources of small vehicles. The methodology consisted of defining the group of vehicles with low performance or are not compatible with high-level known applications; design a reduced, modular, and compatible architecture; design a producer-consumer algorithm that adjusts to the simultaneous localization and communication of multiple vehicles with UWB sensors; validate the operation with an interception task. The results showed the feasibility of performing architecture for embedded systems compatible with other applications managing information through the proposed algorithm allowed to complete the interception task between two vehicles. Another result was to determine the system’s efficiency by scaling the memory size and comparing its performance. The work’s contributions show the areas of opportunity to develop architectures focusing on the optimization of robot resources and complement existing ones.

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Section: Background and Related Workmentioning

confidence: 99%

Sensor Information Sharing Using a Producer-Consumer Algorithm on Small Vehicles

Vazquez-Lopez

Lozada

Sandoval-Gutierrez

et al. 2021

Sensors

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“…This ready-to-use solution controls the flight autonomously, so it can be adopted independently of the application field [9,24,30]. Nevertheless, the potential of using Raspberry Pi platforms as companion computers has also been proven in [8,20]. In both cases, the platform is connected to a Pixhawk autopilot system, while enhancing the flight control by 1) including a neural network to couple a vision-based track system [8] or 2) collaborating with a ground station to build a full distributed 3D position tracking system [20].…”

Section: General-purpose Software-programmable Solutionsmentioning

confidence: 99%

Unmanned Vehicles in Smart Farming: a Survey and a Glance at Future Horizons

Madroñal

Palumbo

Capotondi

et al. 2021

Proceedings of the 2021 Drone Systems Engineering and Rapid Simulation and Performance Evaluation: Methods and Tools Proceeding

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Smart and Precision Agriculture is nowadays already exploiting advanced drones and machinery, but it is foreseen that in the near future more complex and intelligent applications will be required to be brought on-board to improve qualitatively and quantitative production. In this paper, we present an overview on the current usage of autonomous drones in this field and on the augmented computing capabilities that they could count on when companion computers are coupled to flight c ontrollers. T he p aper also present a novel architecture for companion computers that is under development within the Comp4Drones ECSEL-JU project.

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“…In the scientific community, one of the topics of major interest in the UAV field concerns autonomous navigation based on computer vision [1,2]. Many authors have proposed motion capture systems (mocap) [3][4][5][6][7][8], as they guarantee the highest performance. Given the high precision that these systems are able to achieve, they are often used to compare different control techniques.…”

Section: Introductionmentioning

confidence: 99%

“…In order to investigate this new formulation of the problem, the classic UAV architecture shown in Figure 1 and composed of a micro-controller, sensors and a receiver capable of establishing a radio link for the drone commands is no longer sufficient. Instead, it is necessary to use a multilevel architecture, composed of both classic micro-controllers and other boards capable of processing images and complex algorithms, where each level must be able to communicate with the adjacent ones (see, e.g., [4]). As a consequence, the complexity of the drone inevitably increases.…”

Section: Introductionmentioning

confidence: 99%

“…In fact, most of the scientific papers dealing with the development of technology and algorithms for autonomous UAVs use this platform [13]. Among the most important reasons for this choice, two are prominent: (i) the PixHawk board was one of the first and most complete open source platforms for drones; and (ii) some custom versions of the firmware give native support for a robot operating system (ROS), a popular framework for robot development and programming [4]. Indeed, usually on UAVs based on a multilevel hardware, an additional card running ROS is used.…”

Section: Introductionmentioning

confidence: 99%

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A Multilevel Architecture for Autonomous UAVs

Bigazzi

Basso

Boni

et al. 2021

Drones

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In this paper, a multilevel architecture able to interface an on-board computer with a generic UAV flight controller and its radio receiver is proposed. The computer board exploits the same standard communication protocol of UAV flight controllers and can easily access additional data, such as: (i) inertial sensor measurements coming from a multi-sensor board; (ii) global navigation satellite system (GNSS) coordinates; (iii) streaming video from one or more cameras; and (iv) operator commands from the remote control. In specific operating scenarios, the proposed platform is able to act as a “cyber pilot” which replaces the role of a human UAV operator, thus simplifying the development of complex tasks such as those based on computer vision and artificial intelligence (AI) algorithms which are typically employed in autonomous flight operations.

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A Full Distributed Multipurpose Autonomous Flight System Using 3D Position Tracking and ROS

Cited by 12 publications

References 1 publication

Sensor Information Sharing Using a Producer-Consumer Algorithm on Small Vehicles

Sensor Information Sharing Using a Producer-Consumer Algorithm on Small Vehicles

Unmanned Vehicles in Smart Farming: a Survey and a Glance at Future Horizons

A Multilevel Architecture for Autonomous UAVs

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