PRE2018 4 Group3
Group Members
| Name | Student Id |
|---|---|
| Han Wei Chia | 1002684 |
| Niek Brekelmans | 1017203 |
| Floris Verheijen | 0948592 |
| Esmee Esselaar | 0987206 |
| Minjin Song | 1194206 |
Problem statement
In the past few years beekeepers around the world have seen sudden dissapearances of wild and domesticated bees and a steady decline in the amount of honey bee colonies. According to research, causes of the observed decline can be found in the increase in pesticide use around the world and steadily increasing urbanization. Even climate change may be a factor that influences bee population decline.
Since around a third of the global food consumption depends on pollination by insects, of which the bee is a significant contributor, the decline or even extinction of these pollinators would have a large impact on our lives.
Besides proposed solutions to stop further decline of the bee population, there is a need to compensate the already occurred loss of pollinators. In this project, the intent is to research and design a replacement for bee pollination, in the form of a robotic and drone-like bee.
Objective
User, society and enterprise
Users
Due to decreasing population of honey bees in recent years, there has been impacts in beekeeping industries as well as in the rate of pollination by bees. Because significant proportion of food consumption in the world depends on pollination by insects, those who provide materials for food processors definitely needs replacements for the future. Those who are involved in food affected by pollination, such as beekeepers and large scale plant owners whose plants depend on pollination by insects, will be primary users who will definitely consider this solution to be feasible.
At this time, some beekeepers make a living by renting their bees to farms and municipalities that require more pollination. The jobs of those people will be complemented with robotic bees, so their job is saved, even if bees become extinct. Beekeepers will have to focus on repairing the robotic bee, rather than care for actual animals. If beekeepers can hande this shift in their business, they will not be affected by the robotic bee in a negative way.
Society
There are more honey bees in this world than any other type of bee and pollinating insects. This means that honey bees are the most important pollinators of our food crops. Approximately one third of our food relies on the pollination by bees. Without honey bees, we would have a global food crisis that would kill a lot of people. This food shortage in case of an extinction will be prevented if an artificial pollinator replaces bees in time. The protection of our food chain is essential and vital to humanity's survival.
Enterprise
Plants will be in trouble if pollinators die out. A lot of them would go extinct. This would lead to mass disruption of insect and wildlife life cycles. It would be hard to predict exactly what would happen, but there would be many negative impacts on user and society alike. There will be huge demand for other (Artificial) Pollination solution. Robotic bees could be the solution and be very beneficial for enterprises to invest in
Requirements
The things users will require the drones to meet are;
- The reusability of the drones
- They need to be mass producible
- Environment friendly materials need to be used preferably bio degradable
- The drones need to be energy efficient so they last long on one charge
- Easy to control or automated so that 1 person can control multiple drones at once
- During pollination of the flowers the flowers should not be damaged by the drone
- The drones need to be replaceble by one another like real bees are in a swarm
- There must be a way to locate the drones if they break in order to reuse them
Approach
The following appraoch will be used to meet the requirements:
First a literature study will be done on the techniques and requirements described earlier. Next will be a literature study on the current state of the art of artificial pollination. when the research is done a model and/or prototype will be build.
Milestones
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Deliverables
Planning
Our up-to-date planning can be found with the following link: [1].
Assumptions
For our project on robotic bees we decided to narrow down the research and design by focussing on the pollination of apple trees. This was decided since there exist around 300.000 species of flowering plant in the world, making the design a robotic bee suited for all species of flowers too complicated to achieve.
The apple tree was chosen since the apple is the most eaten fruit in the Netherlands, as well as an important export product. Furthermore, when it comes to pollination, the apple tree is self-incompatible, which means that it must be cross-pollinated to bloom. This would accomodate the testing of a prototype of robotic bee, since the self-incompatibility helps to ensure that the bee is the only pollinator.
State of the Art
Pollination
Pollen collection
Honey bees collect pollen as a source of food, used to satisfied the need for protein, minerals and fats. Aside from pollen, honey bees harvest nectar from flowers as part of their diet. While a bee harvests nectar from a plant, the hairs on its body are used to collect pollen from inside the flower. Since the pollen stick to every part of its body, the bee grooms itself with the pollen brush on the back of its legs and collects the pollen in pockets on its hind legs. This is done while the bee is in flight.
Study shows that the density and length of the bees hairs is an important factor in the adhesion of pollen. [1] It is found that the pollen brushes have a hair spacing of 30 micro meter, which results in a hair density of 1100 mm^2. Furthermore it is found that these hairs have a length of 250 micro meter and stand at an angle of 35 degrees with respect to the leg-surface. Subsequently the study shows that there is a strong relation between the pollen size and its adhesion to the hairs. The relation between the diameter of the pollen and the spacing of the bee's hairs defines the difficulty of removal. When the diameter of the pollen is significantly smaller than the spacing of the hairs, the pollen settles deeply into the hairs. However, as the diameter/hair-spacing ration increases, the pollen are suspended between the hairs, which better facilitates the removal of the pollen.
If we want to replicate a bee's hairs as a form of pollen collection, it is required to think of the pollination method. If the goal is to hop from flower to flower and thereby pollinating flowers with the accumulated pollen from one bee, it would be best suited to use a hair setup that easily releases the collected pollen onto a flower. This would mean a patch made up of relatively short hairs, with a high density.
However, if the priority would be to collect the pollen, a set of longer hairs would be required.
Artificial Pollination in Kiwifruit and Olive Trees[2]
In this study, they tested what the best way to collect,store and spread pollen for kiwifruits. Pollen samples were collected with two different systems, but was irrelevant to the conclusion. They timing of when and how to store was more important. Th best way to store to guarantee the highest qualtiy of pollen obtained when the pollen were picked up from the collecting machines about every hour. This is to avoid any stres on the pollen. For short term storage the pollen needed to be stored at 4°C for no more than 7 days. For long tern storage the pollen needed to be stored at −18°C for no more than 3 years low humidity or pre-dried to 10–12% with silica gel at 4°C.
For spreading the pollen they used liquid and dry pollination with varying machines in different flowering stages of the kiwifruit flower. There both as effect if done at the specific flowering. for liquid pollination it was Early Petals Fall and for dry pollination it was Petals Fall.
They used the same technique on olive trees to better understand the moment for pollination in relation to the flowering stage during flowering as they were as they were effective as well.
Pollination efficiency of artificial and bee pollination practices in kiwifruit [3]
In this study they state that the efficiency of artificial pollination has never been compared with that provided by bees and will do so themselves. When comparing bee pollination with artificial. Bee pollination did not only increase the number of kiwifruit produced, but also the number of seeds per fruit, fruit weight and even higher homogeneityin.
Something to also note:
Almost all the fruits produced in the bee-pollinated plants were of export quality while that of artificially pollinated were not.This is because Artificially pollination happened once, when ∼10% of all flowers remained as buds.as for the open flower that were sprayed with pollen, some of them were already senescent. The senescent flowers causes higher chances of producing malformed fruits or no fruit at all.
Effects of natural and artificial pollination on fruit and offspring quality [4]
In this study they research the effects natural and artificial pollination on cape gooseberry. The test the effects of fruit and offspring characteristics on honey and bumble bee pollination compared to manual outcrossing and autonomous self-pollination. Compared to manual and self-pollination, bee pollination increased fruit size, seed set and germination rates. On the other hand , plant growth rate and herbivore resistance were significantly and marginally greater in manually outcrossed plants compared to self-pollinated offspring, suggesting that inbreeding reduces offspring quality. Herbivore resistance and plant growth did not differ between one honeybee visit and self-pollination suggesting that multiple pollinator visits are needed to prevent inbreeding events. bees visitation can significantly alter ecologically and economically relevant traits in this agroecosystem.
Materially Engineered Artificial Pollinators [5]
In this study, multifunctionality from synthesized ionic liquidgels (ILGs) for biotechnology is presented. ILGs exhibit unique properties and coating vertically aligned animal hair with ILGs can be used for effective pollen collection. When place onto a radiowave-controllable UAV it could successfully pollinate L. japonicumflowers.
Development of strawberry pollination system using ultrasonic radiation pressure [6]
In this study they developed an artificial pollination system using ultrasonic radiation pressure as a substitute technique for bee pollination for strawberry cultivation in a plant factory. It has a higher marketable rate than that of no pollination treatment or brush pollination.
(Autonomous) Drones
Autonomous drone is making test flights in Kansas, Illinois [7]
In this project, a drone was created which can fly without an operator or pilot on the scene. It has been created for the purpose of surveillance. This project shows how an autonomous drone which keeps track of a map spawns more than 30 GB of data to fly in an area of around 400 hectares.
Watching the watchmen: Drone privacy and the need for oversight [8]
This paper explores the privacy concerns that is associated with drones and other UAVs. It shows how a 'privacy by design (PbD)' approach helps to ensure that the aqcuired data is protected and the privacy is protected from an early stage of development.
Privacy, data protection and ethics for civil drone practice: A survey of industry, regulators and civil society organisations [9]
This article presents the findings from a survey of the drone industry, regulators and civil society organisations. It uses these results to show that the drone industry is diverse in applications and payloads. The industry sometimes has a lack of knowledge about privacy, ethics and data protection. Operators are often not aware of their obligations within the European law about these subjects. Bringing together watchdogs and regulatory organisations could help to educate drone operators and members of the public.
Experimentally Validated Extended Kalman Filter for UAV State Estimation Using Low-Cost Sensors [10]
Visually based velocity and position estimations can make sure an UAV does not depend on GPS systems. This paper explores a sensor-fusion algorithm, which uses a few different sensors to achieve this. In the experiments, varying parameters were removed in case of different environmental situations. The results show that the velocity and attitude can be estimated, dispite various (indoor) environments.
Wireless charging possibilities
- solar energy
to see if this option is viable first we need to know how much power a micro or nano drone uses. and how much power we can generate from the sun. The power of sunlight per square meter is 1000 W at the surface of the earth. to calculate what the power is that a drone uses 2 sizes of drones were looked into one of 4x4cm and one of 10x10 cm
The 10 by 10 cm drone has 1100 mAh battery with 3.7 V output and can fly for 13 min To be safe we use 10 minutes for the calculation (600 seconds). 1100mAh * 3600 gives 3960000 mA seconds = 3960 A seconds If you divide this by the flight time of 600 seconds you get the current the motors draw from the battery which is 6.6 A to calculate the power the drone uses while flying you multiply the current with the voltage. This gives a power of 24.42 W.
For the nano drone: Its 4 by 4 cm so much smaller however it can’t fly as long as the bigger counterpart, only 5 minutes The battery specifications are 3.7 V output and 100mAh This gives a power of 4.44 W which is a lot less than the bigger drone.
The area of the drones is 0.01 square meter and 0.0016 square meter. if you multiply the power that sunlight has per square meter with the area of the drones you get 10W for the bigger drone and 1.6W for the smaller one. because this is much smaller than the power required and in the most optimal conditions, purfect sunny weather and no clouds or anything this sollution will not work if the motors of the drones do not get more efficient.
- landing platforms
- charge while flying
this problem is currently being solved by GET and they have figured out a way to power drones using modern day techniques. Their solution is to have an elektric net in which the drone can hover to charge. The range in which the drone needs to be is acording to them 10 meters which means that for our project the artificial bees could continue to pollunate flowers while being charged by the network they came up with. They use a large drone for there testing with a rapid chargable battery which can be charged fully in 6 minutes. After charging they can fly 25 minutes with it.
For us this could help a lot by exploiding this solution and creating several (porable)charging locations inside the area where the artificial bees need to pollunate. The website of GET where they have some videos explaning and showing how their tech works (http://getcorp.com/)
Image recognition
Cats or CAT scans: transfer learning from natural or medical image source datasets? [11]
In this article the usefullness of transfer learning is explaned for medical image analysis. Because in medical image analysis there is not much data avaiilable for training a neural network. To do this there was a large amount of data used that had nothing to do with medical images but that could be classified in different cathegories.
Multispectral images of flowers reveal the adaptive significance of using long-wavelength-sensitive receptors for edge detection in bees[12]
In nature bees and other insects need to detect flowers because its their main source of nutrients. They do this by detecting the edges of flowers by using a single type of receptors. the ones for long wavelengths. These receptors gave the highest signal to noise ratio, therefore it would be a good suggestion of what to look for in a camera or method to get an image.
Deap Learning[13]
Deep learning drastically improved visual object recognition in the current state of the art, therefore is it a really good method to use in our project to determine if something is a flower or not without having an operator determining this. multiple examples of types of neural networks are given and how well some perform on images.
Deep Learning of Representations for Unsupervised and Transfer Learning [14]
In the article they discuss the use of unsupervised training of a neural network and how it can bennefit. Especially when training on data that is not from the same cathegorie as the test data
Food image recognition using deep convolutional network with pre-training and fine-tuning [15]
Here a more difficult task is performed, food is being recognised and because types of food sometimes looks a lot like a different type of food this is a more difficult problem than for example determining if there is a cat in a picture. In this article they use a dataset from ImageNet this website also has a lot of flower pictures we could use.
Causes and effects of bee extinction
Climate change: impact on honey bee populations and diseases [16]
In this study the effects of climate change on honey bee behaviour, habitat and disease interaction are discussed. It is found that although the species shows great environmental adaptation capabilities, the added stress of climate change will worsen the factors already endangering the honey bee in certain regions of the world.
Bee declines driven by combined stress from parasites, pesticides, and lack of flowers [17]
The article discusses the causes of honey and wild bee declines. Drivers of declines and colony losses are mentioned to be habitat loss, the increasing use of pesticides, monotonous diets. The article further discusses the potential effect of climate change. Lastly, the authors offer potential solutions for sustainable pollination in the future.
Global pollinator declines: trends, impacts and drivers [18]
The authors of this article discusss the nature and extend of wild and domesticated pollinator declines and its causes. Furthermore, the impact of pollinator decline on wild flower and cultivated crop pollination is discussed, thereby analyzing the economical impact of pollinator losses.
Parallel declines in pollinators and insect-pollinated plants in Britain and the Netherlands [19]
In this article the authors research the decline of local bee diversities in both the Netherlands and Britain. It was found that the largest declines could be seen in nonmigrant and flower specialist species. Furthermore, it was found that plant species relying on the declining polinators were declining in relation to other plant species as well.
Importance of pollinators in changing landscapes for world crops [20]
The authors of the article discuss the importance of pollinators in global agriculture by researching the volume of pollinator dependant food crops and their pollinator dependence level. Furthermore, it was found that agricultural policies and intensification jeopardize pollination stability.
How many flowering plants are pollinated by animals? [21]
In this article the authors research the amount of flowering plants that depend on pollination by animals. It is concluded that in temperate climates 78% and in tropical climates 94% of flowering plant species depend on animal pollination.
Microdrones
In this section, the articles discuss the microdrones and their application and implementation challenges within set area for operation. The purpose of research in this area is to find out how microdrones operate within a specified range for specialized functions, which can be replaced with artificial pollination.
Collaborative Microdrones: Applications and Research Challenges [22]
This article discusses the collaborative application of microdrons specialized for monitoring environmental changes, surveilence, and disaster management. These operations are based on the aerial images provided from the cameras attached to the drones. These drones are also connected to a wireless network, allowing for cooperation to gather data from multiple units of drones for future analysis.
Monitoring CCS Areas using Micro Unmanned Aerial Vehicles [23]
In this article, the author presents a method to develop Micro Unmanned Aerial Vehicles (MUAVs) with the already existing Carbon Capture and Storage technologies to detect leakage of COx gas within the storage area, which requires devices that are mobile and quickly deployable. The author conducts real life experiments within predefined areas for gathering measurements and concludes that the MUAVs are feasible for monitoring.
Unmanned aerial systems for photogrammetry and remote sensing: A review [24]
In this article, the author provides an overview of the development of Unmanned Aerial Vehicles (UAVs) and discusses the state-of-the-art usage of UAVs, specifically photogrammetry and remote sensing. The drones are implemented to provide precise and accurate aerial images which can be used for both photogrammetry and remote sensing within defined areas for operation. The UAVs are also required to communicate to the ground station and with each other to avoid air collisions.
UAV-Based Augmented Monitoring–Real-Time Georeferencing and Integration of Video Imagery with Virtual Globes [25]
This article discusses a completion of virtual globe monitoring with the use of UAVs in areas such as forest fires, traffic, and surveillance. The project uses existing MD4-200 UAV platform with geosensors such as cameras, GPS, and compass and is augmented to virtual globe monitoring. The author concluded that the use of UAVs in the virtual globe is very promising with the data it gathers but also very challenging as real-time processing of the aerial images to models requires a new approach to overcome variables such as weather conditions and lighting.
Analysis of Unmanned Aerial System-Based CIR Images in Forestry—A New Perspective to Monitor Pest Infestation Levels [26]
This article analyzes the use of UAVs to detect pest infestation at a forest. With the color infrared camera attached to the drone, the author was able to determine which trees were infested with pest. The author concluded with positive notes that these implementations of drones will save time and costs and be easy to implement for private forest owners.
Apple
Quality factors
Robotic bee replacements
What should robotic bees replace?
Travel distance
From approximately 12,000 bees studied, the distances of honey bees traveled from their apiary for pollination ranged from 45 meters to almost 6 kilometers.[27] The rate of bees returning to thier apiary of origin decreased exponentially as the travel distance increased from 800 meters. Because robot bees are not only replacing the functions of honey bees but also to improve upon the capabilities of honey bees, the robotic bees will be program to return apiary of origin, which is the charging station.
Carrying capacity
An average honey bee can carry at least 15 miligrams of pollen and make at least 1 million trips per year to collect pollens in order to maintain its colony. [28] Robotic bees with improved carrying capacity should not only carry the minimum amount to maintain but also shorten the amount of time needed to maintain.
Design of an Autonomous Precision Pollination Robot [29]
The article describes the development of the 'BrambleBee', an autonomous robot designd to pollinate bramble plants in a greenhouse environment. It uses mapping of the environment, flower identification and high precision arm control to pollinate bramble flowers.
Autonomous pollination of individual kiwifruit flowers: Toward a robotic kiwifruit pollinator [30]
The paper presents an evaluation of a kiwifruit pollination robot, which is able to pollinate 79,5% of tested kiwifruit flowers. Furthermore, results show that even though several artificially pollinated flowers grew into fruit, the fruit standard was below commercial requirements.
References
- ↑ Honey bee hairs and pollenkitt are essential for pollen capture and removal, Guillermo J Amador et al 2017 Bioinspir. Biomim. 12 026015, https://doi.org/10.1088/1748-3190/aa5c6e
- ↑ Tacconi Gianni and Michelotti Vania (June 6th 2018). Artificial Pollination in Kiwifruit and Olive Trees, Pollination in Plants, Phatlane William Mokwala, IntechOpen, DOI: 10.5772/intechopen.74831. Available from: https://www.intechopen.com/books/pollination-in-plants/artificial-pollination-in-kiwifruit-and-olive-trees
- ↑ Agustín Sáez, Pedro Negri, Matias Viel, Marcelo A. Aizen, Pollination efficiency of artificial and bee pollination practices in kiwifruit Scientia Horticulturae, Volume 246, 2019, Pages 1017-1021, ISSN 0304-4238, http://doi.org/10.1016/j.scienta.2018.11.072.(http://www.sciencedirect.com/science/article/pii/S0304423818308525)
- ↑ Alexander Chautá-Mellizo, Stuart A. Campbell, Maria Argenis Bonilla, Jennifer S. Thaler, Katja Poveda, Effects of natural and artificial pollination on fruit and offspring quality, Basic and Applied Ecology, Volume 13, Issue 6, 2012, Page 524-532, ISSN 1439-1791, https://doi.org/10.1016/j.baae.2012.08.013. (http://www.sciencedirect.com/science/article/pii/S143917911200093X)
- ↑ Svetlana A. Chechetka, Yue Yu, Masayoshi Tange, Eijiro Miyako, Materially Engineered Artificial Pollinators, Chem, Volume 2, Issue 2, 2017, Pages 224-239, ISSN 2451-9294, https://doi.org/10.1016/j.chempr.2017.01.008. (http://www.sciencedirect.com/science/article/pii/S2451929417300323)
- ↑ Hiroshi Shimizu, Taito Sato, Development of strawberry pollination system using ultrasonic radiation pressure, IFAC-PapersOnLine, Volume 51, Issue 17, 2018, Pages 57-60, ISSN 2405-8963, https://doi.org/10.1016/j.ifacol.2018.08.060 (http://www.sciencedirect.com/science/article/pii/S2405896318311765)
- ↑ P. J. Griekspoor, "Autonomous drone is making test flights in Kansas, Illinois," Southwest Farm Press, 2018. Available: https://search.proquest.com/docview/2088344724?accountid=27128
- ↑ Jenkins, Ben. "Watching the watchmen: Drone privacy and the need for oversight." Ky. LJ 102 (2013): 161.
- ↑ Rachel L. Finn, David Wright, "Privacy, data protection and ethics for civil drone practice: A survey of industry, regulators and civil society organisations", Computer Law & Security Review, vol. 32, num. 4, p.p. 577 - 586
- ↑ Driessen, S. P. H., et al. "Experimentally Validated Extended Kalman Filter for UAV State Estimation using Low-Cost Sensors." IFAC-PapersOnLine, vol. 51, no. 15, 2018, pp. 43-48. SCOPUS, www.scopus.com, doi:10.1016/j.ifacol.2018.09.088.
- ↑ Cheplygina, V. (2019). Cats or CAT scans: Transfer learning from natural or medical image source data sets?.
- ↑ Vasas, V., Hanley, D., Kevan, P. and Chittka, L. (2019). Multispectral images of flowers reveal the adaptive significance of using long-wavelength-sensitive receptors for edge detection in bees.
- ↑ LeCun, Y., Bengio, Y. and Hinton, G. (2015). Deep learning. Nature, 521, p.436.
- ↑ Bengio. Y (2012)Deep Learning of Representations for Unsupervised and Transfer Learning JMLR
- ↑ K. Yanai and Y. Kawano, "Food image recognition using deep convolutional network with pre-training and fine-tuning," 2015 IEEE International Conference on Multimedia & Expo Workshops (ICMEW), Turin, 2015, pp. 1-6. doi: 10.1109/ICMEW.2015.7169816 URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7169816&isnumber=7169738
- ↑ Y. Le Conte and M. Navajas, "Climate change: impact on honey bee populations and diseases". (Sept 2008). Revue scientifique et technique (International Office of Epizootics). 27(2). p 499-510.
- ↑ D. Goulson, E. Nicholls, C. Botías, E.L. Rotheray. "Bee declines driven by combined stress from parasites, pesticides, and lack of flowers". (March 2015) Science 347(6229). DOI: 10.1126/science.1255957
- ↑ S.G. Potts, J.C. Biesmeijer, C. Kremen, P. Neumann, O. Schweiger, W.E. Kunin. "Global pollinator declines: trends, impacts and drivers" (June 2010) Trends in Ecology & Evolution 25(6), p 345-353. DOI: 10.1016/j.tree.2010.01.007
- ↑ Biesmeijer, J.C., Roberts, S.P.M.b, Reemer, M.c, Ohlemüller, R.d, e.a. "Parallel declines in pollinators and insect-pollinated plants in Britain and the Netherlands". (July 2006) Science 313(5785), p 351-354. DOI: 10.1126/science.1127863.
- ↑ A.M. Klein, B.E. Vaissière, J.H. Cane, I. Steffan-Dewenter, S.A. Cunningham, C. Kremen, T. Tscharntke. "Importance of pollinators in changing landscapes for world crops" (February 2007) Proceedings of the Royal Society B: Biological Sciences, 274(1608), p 303-313
- ↑ Ollerton, J., Winfree, R., Tarrant, S. "How many flowering plants are pollinated by animals?" (March 2011) Oikos 120(3), p 321-326
- ↑ Quaritsch, Markus & Stojanovski, Emil & Bettstetter, Christian & Friedrich, Gerhard & Hellwagner, Hermann & Rinner, Bernhard & Hofbaur, Michael & Shah, Mubarak. (2008). Collaborative microdrones: Applications and research challenges. 38. 10.1145/1487652.1487690.
- ↑ P.P. Neumann, S. Asadi, V. Hernandez Bennetts, A.J. Lilienthal, M. Bartholmai, Monitoring of CCS Areas using Micro Unmanned Aerial Vehicles (MUAVs), Energy Procedia, Volume 37, 2013, Pages 4182-4190, ISSN 1876-6102, https://doi.org/10.1016/j.egypro.2013.06.320 (http://www.sciencedirect.com/science/article/pii/S1876610213005638)
- ↑ I. Colomina, P. Molina, Unmanned aerial systems for photogrammetry and remote sensing: A review, ISPRS Journal of Photogrammetry and Remote Sensing, Volume 92, 2014, Pages 79-97, ISSN 0924-2716, https://doi.org/10.1016/j.isprsjprs.2014.02.013. (http://www.sciencedirect.com/science/article/pii/S0924271614000501)
- ↑ Eugster, Hannes & Nebiker, Stephan. (2008). UAV-Based Augmented Monitoring–Real-Time Georeferencing and Integration of Video Imagery with Virtual Globes.
- ↑ Lehmann, Jan & Nieberding, Felix & Prinz, Torsten & Knoth, Christian. (2015). Analysis of Unmanned Aerial System-Based CIR Images in Forestry—A New Perspective to Monitor Pest Infestation Levels. Forests. 6. 594-612. 10.3390/f6030594.
- ↑ Hagler, J. R., Mueller, S., Teuber, L. R., Machtley, S. A., & Van Deynze, A. (2011). Foraging range of honey bees, Apis mellifera, in alfalfa seed production fields. Journal of insect science (Online), 11, 144. doi:10.1673/031.011.14401
- ↑ Winston, Mark L. (1987). The biology of the honey bee. Cambridge, Mass: Harvard University Press, 177
- ↑ N. Ohni, K. Lassak, R. Watson, J. Strader, Y. Du e.a. "Design of an Autonomous Precision Pollination Robot". (Dec 2018) 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems, Madrid. DOI: 10.1109/IROS.2018.8594444
- ↑ H. Williams, M. Nejati, S. Hussein, N. Penhall, J.Y. Lim, e.a. "Autonomous pollination of individual kiwifruit flowers: Toward a robotic kiwifruit pollinator" (2019) Journal of Field Robotics. DOI: 10.1002/rob.21861