Robust Positioning of Drones for Land Use Monitoring in Strong Terrain Relief Using Vision-Based Navigation

Kupervasser, Oleg; Sarychev, Vitalii; Rubinstein, Alexander; Yavich, Roman

doi:10.21660/2018.45.7322

Cited by 5 publications

(5 citation statements)

References 15 publications

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“…Robots can undertake repetitive tasks, support manual work and service customers at unsociable hours. Drones and CAVs have a range of applications from servicescape monitoring, data gathering, visitor guidance to remote service delivery and integrated transportation service systems within broader smart environments (Kupervasser et al , 2018). They can be used to deliver products in areas where no infrastructure is required.…”

Section: Technology-driven Disruptions For Service Industry Structuresmentioning

confidence: 99%

Technological disruptions in services: lessons from tourism and hospitality

Buhalis

Harwood

Bogicevic

et al. 2019

JOSM

556

263

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Purpose Technological disruptions such as the Internet of Things and autonomous devices, enhanced analytical capabilities (artificial intelligence) and rich media (virtual and augmented reality) are creating smart environments that are transforming industry structures, processes and practices. The purpose of this paper is to explore critical technological advancements using a value co-creation lens to provide insights into service innovations that impact ecosystems. The paper provides examples from tourism and hospitality industries as an information dependent service management context. Design/methodology/approach The research synthesizes prevailing theories of co-creation, service ecosystems, networks and technology disruption with emerging technological developments. Findings Findings highlight the need for research into service innovations in the tourism and hospitality sector at both macro-market and micro-firm levels, emanating from the rapid and radical nature of technological advancements. Specifically, the paper identifies three areas of likely future disruption in service experiences that may benefit from immediate attention: extra-sensory experiences, hyper-personalized experiences and beyond-automation experiences. Research limitations/implications Tourism and hospitality services prevail under varying levels of infrastructure, organization and cultural constraints. This paper provides an overview of potential disruptions and developments and does not delve into individual destination types and settings. This will require future work that conceptualizes and examines how stakeholders may adapt within specific contexts. Social implications Technological disruptions impact all facets of life. A comprehensive picture of developments here provides policymakers with nuanced perspectives to better prepare for impending change. Originality/value Guest experiences in tourism and hospitality by definition take place in hostile environments that are outside the safety and familiarity of one’s own surroundings. The emergence of smart environments will redefine how customers navigate their experiences. At a conceptual level, this requires a complete rethink of how stakeholders should leverage technologies, engage and reengineer services to remain competitive. The paper illustrates how technology disrupts industry structures and stimulates value co-creation at the micro and macro-societal level.

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Section: Technology-driven Disruptions For Service Industry Structuresmentioning

confidence: 99%

Technological disruptions in services: lessons from tourism and hospitality

Buhalis

Harwood

Bogicevic

et al. 2019

JOSM

556

263

View full text Add to dashboard Cite

show abstract

“…In this paper, we describe correct operation of autopilot for supply desirable drone flight (movement of a drone in a vertical plane at a constant height). For the finding drone, flight parameters were used vision-based navigation [11][12][13][14][15][16][17][18][19][20]. For realization vision-based navigation was developed the computer program "Video-navigation of UAV over relief" [11].…”

Section: The Adaptation Of This Mathematical Theory For Dronementioning

confidence: 99%

“…For realization vision-based navigation was developed the computer program "Video-navigation of UAV over relief" [11]. This program was tested in Zhejiang Province in east China near the capital Hangzhou using Google Earth data [17]. There always exists a noticeable delay in getting information about position and orientation of a drone to autopilot for vision-based navigation because of computer processing image's big data.…”

Section: The Adaptation Of This Mathematical Theory For Dronementioning

confidence: 99%

A method for stabilization of drone flight controlled by autopilot with time delay

et al. 2020

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In this paper, the methods of the stability theory of differential equations with time delays are used in the study of an actual engineering problem of a drone (UAV) autonomous flight. We describe correct operation of autopilot for supply stability of desirable drone flight. There exists a noticeable delay in getting information about position and orientation of a drone to autopilot in the presence of vision-based navigation (visual navigation). In spite of this fact, we demonstrate that it is possible to provide stable flight at a constant height in a vertical plane. We describe how to form relevant controlling signal for autopilot in the case of the navigation information delay and provide control parameters for particular case of flight.

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“…Unmanned autonomous robots will be widely used very soon for land use, treatment, and monitoring [1][2][3]. The most popular outdoor robots are currently robot-lawnmowers used for bounded operation area.…”

Section: Introductionmentioning

confidence: 99%

The New Advanced Prototype of Airborne Visual Control of a Ground Robot

Kupervasser¹

2021

GEOMATE

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Unmanned autonomous robots will be widely used very soon for land use, treatment, and monitoring. The paper addresses the problem of visual navigation of ground robots using a camera positioned at a certain elevation above the confined area. The main idea is that robot's "eyes" is not located on the robot but are independent autonomous system. As a result, the "eyes" can go up and observe the robot from above. This patented technology of airborne vision-based control of ground robots is already described previously in "International Journal of GEOMATE" and Geomate2019 conference paper (Ehrenfeld et al., 2020). There was described in detail the small toy prototype with very simple algorithms and very shortly the next more complex prototype. In the current paper detailed algorithms for navigation and control of this complex prototype is presented. The system consists of the USB camera on the tower (4 meters) connected to the computer which controls the big ground robot by sending Wi-Fi commands. For navigation (recognition of the ground robot, finding its position and orientation) was used deep learning (artificial neural network). It was demonstrated that this robot can pass two main tests: travelling along some predefined path and random walk inside of some predefined boundary.

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Robust Positioning of Drones for Land Use Monitoring in Strong Terrain Relief Using Vision-Based Navigation

Cited by 5 publications

References 15 publications

Technological disruptions in services: lessons from tourism and hospitality

Technological disruptions in services: lessons from tourism and hospitality

A method for stabilization of drone flight controlled by autopilot with time delay

The New Advanced Prototype of Airborne Visual Control of a Ground Robot

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