Vision algorithms for fixed-wing unmanned aerial vehicle landing system

Fan, Yanming; Ding, Meng; Cao, Yunfeng

doi:10.1007/s11431-016-0618-3

Cited by 23 publications

(11 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…[8]. The learning model has been widely applied to the manufacturing environment for image recognition [27,28], equipment monitoring, diagnosis [29][30][31], etc.…”

Section: Typical Ai Modelsmentioning

confidence: 99%

Smart additive manufacturing: Current artificial intelligence-enabled methods and future perspectives

Wang

Zheng

Peng

et al. 2020

Sci. China Technol. Sci.

View full text Add to dashboard Cite

Additive manufacturing (AM) has been increasingly used in production. Because of its rapid growth, the efficiency and robustness of AM-based product development processes should be improved. Artificial intelligence (AI) is a powerful tool that has outperformed humans in numerous complex tasks. AI-enabled intelligent agents can reduce the workforce required to scale up AM production and achieve higher resource utilization efficiency. This study provides an introduction of AI techniques. Then, the current development of AI-enabled AM product development is investigated. Existing intelligent agents are used for problems in product design, process design and production stages. Based on the review, current research gaps and future research directions are identified. To guide future development of more efficient and comprehensive intelligent agents, a smart AM framework based on cloud-edge computing is proposed. Global consideration can be realized in the cloud environment, and a fast response can be achieved at the edge nodes. additive manufacturing, artificial intelligence, product development, cloud-edge computing

show abstract

“…[8]. The learning model has been widely applied to the manufacturing environment for image recognition [27,28], equipment monitoring, diagnosis [29][30][31], etc.…”

Section: Typical Ai Modelsmentioning

confidence: 99%

Smart additive manufacturing: Current artificial intelligence-enabled methods and future perspectives

Wang

Zheng

Peng

et al. 2020

Sci. China Technol. Sci.

View full text Add to dashboard Cite

show abstract

“…This airspeed is generated by the forward thrust produced usually by a propeller turned by an electric motor. It is mainly characterized by its high cruise speed and long endurance and is mostly used for long distance, long range and high altitude missions (e.g., [38][39][40][41]). Two models of fixed-wing UAVs are illustrated in Figure 5 (see a.1 and a.2).…”

Section: Class Of Uavmentioning

confidence: 99%

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

2019

View full text Add to dashboard Cite

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.

show abstract

“…Unlike rotary wings, fixed wings requires landing strips and a trained pilot to operates the platform. Even with autonomous flight features, fixed wings still requires experts in landing and take-off since it don't have the vertical take-off and landing (VTOL) ability (Fan et al, 2017). Fixed wing platforms only take the advantage of high lift-to-drag ratio, fuel-efficient flying, and high-speed flying, making it a good consideration in aerial mapping.…”

Section: Fixed Wingsmentioning

confidence: 99%

Aerial Platform Reliability for Flood Monitoring Under Various Weather Conditions: A Review

Zakaria

Mahadi

Abdullah

et al. 2018

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

View full text Add to dashboard Cite

<p><strong>Abstract.</strong> Flood is an annual disaster in Malaysia, especially in the east coast region. Recently, other regions in Malaysia have also experience devastating flood. A flood aerial monitoring is one of the approaches that involved in the flood disaster management. Compared to space borne remote sensing, aerial platforms are much reliable to obtain higher spatial resolution and real time data. Due to cloud coverage and revisit limitations, space borne remote sensing approach is a less desirable option for flood monitoring. In this paper, a review of existing aerial platforms that perform remote sensing task under various weather conditions, specifically for flood monitoring is presented. There are four types of aerial platforms being reviewed, which are rotary wings, fixed wings, blimps and helikites. The main criteria of the review are the payload capacity, endurance (flight time), altitudes, tolerable wind speed, cost, vertical take-off and landing ability, and the ability to perform under various weather conditions, such as heavy precipitation and winds. From this review, the applications of aerial platform in recent studies never mentioned the capability of aerial platform used in such weather conditions. From all types of aerial platform discussed, helikite seems to be the most suitable to fly in extreme weather. The only drawback is that helikite has mobility issue since it is tethered to the ground. The application of helikite is useful for a small area coverage of flood monitoring. The authors will continue the study to evaluate the reliability of helikite in performing such task in the future.</p>

show abstract

Vision algorithms for fixed-wing unmanned aerial vehicle landing system

Cited by 23 publications

References 13 publications

Smart additive manufacturing: Current artificial intelligence-enabled methods and future perspectives

Smart additive manufacturing: Current artificial intelligence-enabled methods and future perspectives

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

Aerial Platform Reliability for Flood Monitoring Under Various Weather Conditions: A Review

Contact Info

Product

Resources

About