Visual Based Landing for an Unmanned Quadrotor

Cocchioni, Francesco; Frontoni, Emanuele; Ippoliti, Gianluca; Longhi, Sauro; Mancini, Adriano; Zingaretti, Primo

doi:10.1007/s10846-015-0271-6

Cited by 23 publications

(12 citation statements)

References 13 publications

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“…Landing UAVs on a service charging station is realized with the help of various systems of navigation and analysis of the surrounding area. The paper [8] describes the vision system developed for target detection and tracking. Adopted an optimized solution to save computation time ensuring a real time image processing supported by the robot operating system environment.…”

Section: Electromechanical Maintenance Systems For Unmanned Aerial Vementioning

confidence: 99%

Classification of robotic battery service systems for unmanned aerial vehicles

2018

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Abstract.Existing examples of prototypes of ground-based robotic platforms used as a landing site for unmanned aerial vehicles are considered. In some cases, they are equipped with a maintenance mechanism for the power supply module. The main requirements for robotic multi-copter battery maintenance systems depending on operating conditions, required processing speed, operator experience and other parameters are analyzed. The key issues remain questions of the autonomous landing of the unmanned aerial vehicles on the platform and approach to servicing battery. The existing prototypes of service robotic platforms are differed in the complexity of internal mechanisms, speed of service, algorithms of joint work of the platform and unmanned aerial vehicles during the landing and maintenance of the battery. The classification of robotic systems for servicing the power supply of multi-copter batteries criteria is presented using the following: the type of basing, the method of navigation during landing, the shape of the landing pad, the method of restoring the power supply module. The proposed algorithmic model of the operation of battery power maintenance system of the multi-copter on ground-based robotic platform during solving the target agrarian problem is described. Wireless methods of battery recovery are most promising, so further development and prototyping of a wireless charging station for multi-copter batteries will be developed.

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Section: Electromechanical Maintenance Systems For Unmanned Aerial Vementioning

confidence: 99%

Classification of robotic battery service systems for unmanned aerial vehicles

2018

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“…Jeon et al [10] presented a real-time visionguided control algorithm (detection and tracking) for an UAV using CUDA-enabled GPU cards. Cocchioni et al [11] also showed the implementation of visual-based landing for an unmanned quadrotor using a NVIDIA Tegra Jetson K1.…”

Section: Introductionmentioning

confidence: 99%

On-Board High-Performance Computing For Multi-Robot Aerial Systems

Forero¹,

Chic²,

Menéndez³

2017

Aerial Robots - Aerodynamics, Control and Applications

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With advancements in low-energy-consumption multi/many core embedded-computing devices, a logical transition for robotic systems is Supercomputing, formally known as high performance computing (HPC), a tool currently used for solving the most complex problems for humankind such as the origin of the universe, the finding of deceases' cures, etc. As such, HPC has always been focused on scientific inquires. However, its scope can be widening up to include missions carried out with robots. Since a robot could be embedded with computing devices, a set of robots could be set as a cluster of computers, the most reliable HPC infrastructure. The advantages of setting up such an infrastructure are many, from speeding up on-board computation up to providing a multi-robot system with robustness, scalability, user transparency, etc., all key features in supercomputing. This chapter presents a middleware technology for the enabling of high performance computing in multi-robot systems, in particular for aerial robots. The technology can be used for the automatic deployment of cluster computing in multi-robot systems, the utilization of standard HPC technologies, and the development of HPC applications in multiple fields such as precision agriculture, military, civilian, search and rescue, etc.

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“…Vision-Based Control: The aircraft's position and orientation are controlled on the basis of the information captured by vision sensors and subsequently processed by computer vision algorithms (e.g., [20][21][22]). The vision-based control of UAVs began in the 1990s.…”

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confidence: 99%

“…List of the most popular publication venues.Journal of Intelligent & Robotic Systems23 15.97%[18,20,27,30,40,51,68,69,71,73,[83][84][85][86][87][88][89][90][91][92][93][94][95] …”

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confidence: 99%

Computer Vision in Autonomous Unmanned Aerial Vehicles—A Systematic Mapping Study

2019

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Personal assistant robots provide novel technological solutions in order to monitor people’s activities, helping them in their daily lives. In this sense, unmanned aerial vehicles (UAVs) can also bring forward a present and future model of assistant robots. To develop aerial assistants, it is necessary to address the issue of autonomous navigation based on visual cues. Indeed, navigating autonomously is still a challenge in which computer vision technologies tend to play an outstanding role. Thus, the design of vision systems and algorithms for autonomous UAV navigation and flight control has become a prominent research field in the last few years. In this paper, a systematic mapping study is carried out in order to obtain a general view of this subject. The study provides an extensive analysis of papers that address computer vision as regards the following autonomous UAV vision-based tasks: (1) navigation, (2) control, (3) tracking or guidance, and (4) sense-and-avoid. The works considered in the mapping study—a total of 144 papers from an initial set of 2081—have been classified under the four categories above. Moreover, type of UAV, features of the vision systems employed and validation procedures are also analyzed. The results obtained make it possible to draw conclusions about the research focuses, which UAV platforms are mostly used in each category, which vision systems are most frequently employed, and which types of tests are usually performed to validate the proposed solutions. The results of this systematic mapping study demonstrate the scientific community’s growing interest in the development of vision-based solutions for autonomous UAVs. Moreover, they will make it possible to study the feasibility and characteristics of future UAVs taking the role of personal assistants.

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Visual Based Landing for an Unmanned Quadrotor

Cited by 23 publications

References 13 publications

Classification of robotic battery service systems for unmanned aerial vehicles

Classification of robotic battery service systems for unmanned aerial vehicles

On-Board High-Performance Computing For Multi-Robot Aerial Systems

Computer Vision in Autonomous Unmanned Aerial Vehicles—A Systematic Mapping Study

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