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==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. <ref> 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 </ref> 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<ref>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</ref> ===

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 <ref>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) </ref> ===

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 <ref>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)</ref> ===

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 <ref>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)</ref> ===

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 <ref>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)</ref> ===

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 <ref> 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</ref> ===

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 <ref>Jenkins, Ben. "Watching the watchmen: Drone privacy and the need for oversight." Ky. LJ 102 (2013): 161.</ref> ===


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 <ref> 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</ref> ===

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 <ref>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.</ref> ===

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? <ref>Cheplygina, V. (2019). Cats or CAT scans: Transfer learning from natural or medical image source data sets?.

</ref>===

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<ref>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.</ref>===

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<ref>LeCun, Y., Bengio, Y. and Hinton, G. (2015). Deep learning. Nature, 521, p.436.</ref>===
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 <ref>Bengio. Y  (2012)Deep Learning of Representations for Unsupervised and
Transfer Learning JMLR</ref> ===

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 <ref>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
</ref>===

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 <ref>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.</ref>===

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 <ref> 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 </ref> ===

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 <ref> 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 </ref> ===

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 <ref> 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. </ref> ===

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 <ref> 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 </ref> ===

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? <ref> Ollerton, J.,  Winfree, R.,  Tarrant, S.  "How many flowering plants are pollinated by animals?" (March 2011) Oikos 120(3), p 321-326 </ref> ===

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 <ref> 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. </ref> ===
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 <ref> 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) </ref> ===
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 CO{{sub|2}} 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 <ref> 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) </ref>=== 
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 <ref> Eugster, Hannes & Nebiker, Stephan. (2008). UAV-Based Augmented Monitoring–Real-Time Georeferencing and Integration of Video Imagery with Virtual Globes. </ref>===
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 <ref> 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. </ref> ===
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===
Consumers assess an apples appearance by its colour, size, shape, absence of defects and then by its eating quality. There are 3 groups of factors affecting the quality: Genetic, Environmental and Agronomic factors.

Quality of a apple is strictly linked to its dna, there are many strains of apples that has been produced in cultivation by selective breeding(Delicious,Gala,Fuji,Golden Delicious,Jonathan,Rome)

Apples should be grown environments that are most suited for the strain apple, this will produce higher quality apples. The most important environmental factors for high quality apples are temperature and light.

Apples are highly temperature-responsive in the first 40 days after pollination. Fruit expansion was 10 times greater at a mean temperature of 20 °C than at a mean of 6 °C.<ref>Warrington, I.J., Fulton, T.A., Halligan, E.A., de Silva, H.N., 1999. Apple fruit growth and maturity are affected by early season temperatures</ref>

Light and fruit quality are strongly associated. if high quality commercial apples get less than 50% of the total light energy they usually get, they won't develop. However, fruit exposed to high levels of light will cause some defects, such as bitter pit, internal breakdown and rotting. Areas characterized by high light intensity and temperature can also present sunburn problems. In the temperate zone, it is possible to lose from 5 to 10% of apples due to sunburn damage.<ref>Schrader, L.E., Felicetti, D.A., Sun, J., Xu, J.-Z., Zhang, J.-G., Kahn, C.B., 2008. Effects of high temperature and high solar irradiance on sunburn fruit quality, and skin pigments of apple</ref> The most common of the sunburns is browning, it results in a yellow/bronze colouration of the apple. This doesn't affect the flesh of the apple itself but when fruit surface temperature reaches about 52 degrees.<ref>Schrader, L.E., Felicetti, D.A., Sun, J., Xu, J.-Z., Zhang, J.-G., Kahn, C.B., 2008. Effects of high temperature and high solar irradiance on sunburn fruit quality, and skin pigments of apple</ref> The flesh of the apple starts to die out. 

Wind velocity plays a role in sunburn. demonstrated that a wind speed increase from 0.3 m s−1 to 4ms−1 reduced the fruit surface temperature by 5 °C  <ref>Thorpe, M.R., 1974. Radiant heating of apples. J. Appl. Ecol.</ref>

Reported that seeds in different apples (‘Golden Delicious’, ‘Annurca’ and ‘Red Delicious’) are able to affect also fruit weight, firmness, acidity, calcium concentration and ripening. <ref>Buccheri, M., Di Vaio, C., 2004. Relationship among seed number, quality, and calcium content in apple fruits. J. Plant Nutr. 27 (10), 1735–1746.</ref>

== 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.<ref> 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 </ref> 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. <ref> Winston, Mark L. (1987). The biology of the honey bee. Cambridge, Mass: Harvard University Press, 177 </ref> 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 <ref> 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 </ref> ===

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 <ref> 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 </ref> ===

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.