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Aide, T.M. et al. (2013), Deforestation and Reforestation of Latin America and the Caribbean (2001-2010) BIOTROPICA 45(2): 262-271 Retrieved from: 10.1111/j.1744-7429.2012.00908.x
Aide, T.M. et al. (2013), Deforestation and Reforestation of Latin America and the Caribbean (2001-2010) BIOTROPICA 45(2): 262-271 Retrieved from: 10.1111/j.1744-7429.2012.00908.x
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=== Current deforestation and combat methods ===
=== Current deforestation and combat methods ===
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=== Current use of Robotics Technology in seeding/reforestation activities ===
=== Current use of Robotics Technology in seeding/reforestation activities ===


The use of machinery in agriculture, the logging industry and nature upkeep is commonplace, however the application of autonomous robotic technology is still rather in its infancy. Some robotics solutions exist in these field, which are primarily categorised in 2 classes: a mobile robotic class and a drone class. Examples in the mobile robotic class include the R-Stepps project (Mohamed, Flavien & Pierre, 2015) <ref> Mohamed, Z., Flavien, V., & Pierre, B. (2015, October). Mobile robotics for restoring degraded ecosystems. In Global Humanitarian Technology Conference (GHTC), 2015 IEEE (pp. 273-278). IEEE. https://doi.org/10.1109/GHTC.2015.7343984 </ref> and the Agribot (Pavan et al., 2017) <ref> Pavan, T. V., Suresh, R., Prakash, K. R., & Mallikarjuna, C. (2017). Design and Development of Agribot for Seeding. </ref>. Examples in the drone class include the Treek'lam (Sinalkar & Phade, 2016) <ref> Sinalkar, S., & Phade, G. (2016, December). Treek'lam. In Global Trends in Signal Processing, Information Computing and Communication (ICGTSPICC), 2016 International Conference on (pp. 611-614). IEEE. https://doi.org/10.1109/ICGTSPICC.2016.7955373 </ref>  
The use of machinery in agriculture, the logging industry and nature upkeep is commonplace, however the application of autonomous robotic technology is still rather in its infancy. Some robotics solutions exist in these field, which are primarily categorised in 2 classes: a mobile robotic class and a drone class. Examples in the mobile robotic class include the R-Stepps project to combat desertification (Mohamed, Flavien & Pierre, 2015) <ref> Mohamed, Z., Flavien, V., & Pierre, B. (2015, October). Mobile robotics for restoring degraded ecosystems. In Global Humanitarian Technology Conference (GHTC), 2015 IEEE (pp. 273-278). IEEE. https://doi.org/10.1109/GHTC.2015.7343984 </ref> and the Agribot to plant seeds on farming land (Pavan et al., 2017) <ref> Pavan, T. V., Suresh, R., Prakash, K. R., & Mallikarjuna, C. (2017). Design and Development of Agribot for Seeding. </ref>. Examples in the drone class include the Treek'lam (Sinalkar & Phade, 2016) <ref> Sinalkar, S., & Phade, G. (2016, December). Treek'lam. In Global Trends in Signal Processing, Information Computing and Communication (ICGTSPICC), 2016 International Conference on (pp. 611-614). IEEE. https://doi.org/10.1109/ICGTSPICC.2016.7955373 </ref> and 


== Project pages ==
== Project pages ==

Revision as of 10:59, 5 May 2018

Group members

  • David van den Beld, 1001770
  • Gerben Erens, 0997906
  • Luc Kleinman, 1008097
  • Maikel Morren, 1002099
  • Adine van Wier, 0999813

Project

Project Statement

The problem of deforestation is one of tremendous scale, and therefore exploration of multiple solutions to it is a necessity. Combatting deforestation can be done in 2 ways, either by reduction of the amount of trees being chopped down, or by increasing the amount of new trees being grown. As the latter is the one which is most likely to be achievable by means of technology than the first, our focus will be on increasing the amount of new trees being grow. This project investigates whether the robotics could be used to effectively to this extend. To accomplish this we envision a robotic vehicle which at least the following 3 technological aspects:

I. A way to check whether or not the soil is fertile, and thus fit to plant a new forest.

II. A device capable of planting the seeds deep enough in the ground to ensure good growing chances for the seed.

III. A way to transport itself around, which will most likely result in wheels, as this is the most achievable option within this course.

This envisioned robot leads to the first and main objective of this project: a prototype. This prototype will feature the before mentioned technological aspects, with the main focus being on aspects I and II, as these are technologies more specific to our envisioned robot. Beyond this, we aim to make a model based around the physics working on the robot, which can help us gain more theoretical insight in the working of the robot. Whilst doing this, we want to do research considering this robots influence on society, and how society can stimulate the development of this technology, considering both society as a whole, and the governments influence separately. Also, the relation between this product and the enterprises interested in it has to be research, as most of the technology will have to come from them, and they might be a big investor.


Planning

Below follows the planning for the project for the upcoming 9 weeks constituting the course 0LAUK0 Project: Robots Everywhere

Table 1: Preliminary planning for the project
Week number Task Person*
1
Choose definitive subject Collaborative effort of all members
Define problem statement and objectives David
Define users Adine
Obtain user requirements Gerben
Work out typical use cases Luc
Define the milestones and deliverables Maikel
Define the approach of the problem Collaborative effort of all members
Search for relevant state-of-the-art (SotA) sources, categories:
  1. Modularity
  2. (Semi-) Autonomous cars
  3. Sensors for prospecting/evaluating ground
  4. Drilling/plowing/seeding mechanism
  5. Current Forestation combat methods
All divided into the subcategories:
  1. Maikel
  2. David
  3. Luc
  4. Gerben
  5. Adine
Make project planning Collaborative effort of all members
2
Review user requirements and use cases Collaborative effort of all members
Finish collecting SotA articles and write SotA section Each member for their respective subcategory
Compile list of potential robot designs Collaborative effort of all members
Make some concept design sketches Maikel
Make a preliminary list of required parts Gerben
Define embedded software environment Luc
Preliminary elimination session for designs based on user requirements Adine
Start compiling list of design preferences/requirements/constraints David
3
Finish list of preferences/requirements/constraints Adine
Further eliminate designs due to constraints Collaborative effort of all members
Rank remaining designs and select a winner Collaborative effort of all members
Develop a building plan/schemata for the winner design Gerben, Luc
Start acquiring physical quantities for modelling design Maikel, David
Start with a simple model of some system parameters Maikel, David
4
Commence robot assembly according to highest priority of building schemata Gerben, David
Continue modelling/simulating Maikel
Start coding robot functionalities Luc
Catch up on documenting the wiki Adine
5
Continue robot assembly and coding Gerben, David, Luc
Continue modelling/simulating Maikel
Catch up on documenting the wiki Collaborative effort of all members
6
Continue robot assembly and coding Gerben, Luc
Test the first (few) finished sub-system(s) of the robot. Collaborative effort of all members
Finish modelling/simulating Maikel, David
Finish catching up on documenting the wiki Collaborative effort of all members
7
Finish robot assembly Gerben
Make concept designs for possible modules Luc
Make a draft for final presentation Maikel, David, Adine
Test the first (few) finished sub-system(s) of the robot. Collaborative effort of all members
8
Buffer time Collaborative effort of all members
Finish final presentation Maikel, David, Adine
Complete wiki Gerben, Luc

* The current division of task is a rough estimate for the next 7 weeks. New tasks may pop up or task division may be rotated, and is hence subject to change during the progress of the course.

Approach

The problem will be approached by a design question. What is the best design for a robot to combat deforestation which will be build modular so that it can be implemented for other purposes with minor changes. The first 2 weeks the approach will primarily be sequential, as user analysis, use cases and requirements/preferences/constraints need to be done sequentially before the rest of the project can start. Once this is over, the project will run in a parallel fashion where building and modelling will happen simultaneously.

Milestones and Deliverables

Table 2: Milestones
Date Accomplished
30-04-2018 SotA research done
03-05-2018 User analysis/use cases done
07-05-2018 Have a partially eliminated list of designs
10-05-2018 Pick final “winner” design
21-05-2018 Have the first working subsystem
25-05-2018 Finish modelling
31-05-2018 Have an operational prototype running
with at least 2 subsystems
07-06-2018 Made several concepts for modules
11-06-2018 Presentation is finished
14-06-2018 Wiki is completely updated

Literature Review

The literature review was divided into 5 subcategories, the results of which will be extended below.

Modularity

Modular robotics is a useful tool in the design of robots for in-field applications, as building a functional specialised robot from scratch is a time-consuming and cost-intensive process. If a modular design approach is taken, the costs of designing a robot could be severely reduced as one general robotic platform with some general functionalities would serve as the starting point, upon which modules can be placed to give the end-product the desired capabilities. A drawback of this modular design method, however, is that the design space will expand explosively due to the seemingly limitless possible configurations the robot could have (Farritor & Dubowsky, 2001) [1]. However, this design space can be brought to proportions by severely reducing it, by placing the constraints which arise from the task to be completed by the robot onto the possible configurations (Farritor & Dubowsky, 2001) [1]. By doing so any and all designs with but a singular deviation which would compromise the execution of the task are immediately discarded in the earlier stages of development.

Some examples of robots which implemented a modular design and with similar environmental working conditions as our to-be-designed seeding robot include the Small Robotic Farm Vehicle (Bawden et al., 2014) [2], the 4-wheel steering weed detection robot of Bak and Jakobsen (Back & Jakobsen, 2004) [3], the Amphibious Locomotion Robot of Li, Urbina, Zhang and Gomez (Li et al., 2017) [4] and the Reconfigurable Integrated Multi-Robot Exploration System (RIMRES) [5]. These robots have in common that they are mostly based on a singular platform, suspended by wheels for locomotion, upon which several modules (e.g. sensors, mechatronic arms, pay-loads, other deployable robots, etc.) can be placed to increase functionality.

A special class of modular robots are the so-called self-reconfigurable modular robots which can change their shape to comply with dynamic environmental constraints and task requirements. Some examples of these self-reconfigurable robots include the I(CES) cubes (Unsal, Kiliccote and Khosla, 1999) [6], M-TRAN (Murata et al., 2002) [7], ATRON (Jorgensen, Ostergaard & Lund, 2004) [8], Modular Robot for Exploration and Discovery (ModRED) (Baca et al., 2014) [9], Polybot (Yim et al., 2003) [10]. Albeit this is an interesting topic of research, for our problem at hand it will not be a feasible solution, since most of these systems are on a mesoscale application, whereas the to-be-designed deforestation robot will be a macroscale prototype.

(Semi)-Autonomous Cars

The patent on remote control systems granted to Mitsubishi Electric Crop. By the US government. This document is a thorough description of how remote control systems work, listing the necessary parts with the movement detector sensor, transmitter, receiver and a potential display device being the main important ones. (Hashimoto et al., 1996) [11]

In this article Elon Musk describes his vision for the autonomous car in 2016, even though this year has already passed, it still shows the vision of one of the main developers of autonomous cars. Elon Musk describes certain aspects of autonomous cars, like the mileage on one charge and the way current non-autonomous cars can be turned into autonomous cars by using a software update only. (Kessler, 2015) [12]

To get our car driving smoothly, we will probably utilize a remote control, meaning that it will be very closely related to a remote controlled toy car, to which this doc. is the current active patent. It shows the state of the art radio controlled toy car technology currently available. (Matsushiro, 1984) [13]

One aspect of the autonomous cars is the intelligent pathing. Using communication with other vehicles, a map of dense traffic places can be made, resulting in an optimal route for the car to take. Obstacles are also communicated between different vehicles. (Bagloee, 2016) [14]

A guide to help us control a servo motor with our computer, as a servo motor is the most likely option if we want our car to drive without outside help. It shows how to program and control a servo motor and how to implement one in the electronic circuit. [15]

A short article on the workings of servo motors, the main two interesting reads are the control of the servo and the different types, as we will have to choose one if we opt to use servo’s to drive our car around. (Jameco Electronics, )[16]

Even though this site is a webshop, and not a scientific article, it shows what technology we can buy within a respectable price range and thus shows what we do not need to make ourselves. Before we start thinking about how to make a part of our robot, lets first check what this shop has got. [17]

Sensors for prospecting/evaluating ground

Evaluating the soil the robot is on can be the defining factor whether it is worth it to plant new seeds in the ground, since an infertile soil will not create a new healthy forest. The design of the robot would benefit from such sensors, since it can utilize this information to determine where to plant the seeds.

Currently the soil can be read with a multitude of sensors. The most simple, but ineffective for our robot, sensor would be to use a simple plant[18] and determine whether the plant shows sufficient growth. A lot of information can be obtained from the plant, like the salinity, nutrients and available soil moisture.

This is however very inefficient and not desirable for our robot. An alternative would be to use moisture sensors[19] to determine the amount of water in the ground, since water is a critical component for a plant to grow. Further sensors include NIR reflectance sensors. These sensors can accurately measure the organic matter within the soil. This leads to an accurate picture whether the soil is fertile enough to plant seeds.

Vis-NIR sensors can also determine the amount of nitrogen and moisture in the soil. Which leads to an even more complete picture of the soil.

Humidity in the air can also help determine whether the area is suitable. An RH sensor[20] based on a Bragg grating can determine the relative humidity accurately. The optical fiber used to determine this can also house temperature, pH, pressure and more sensors. This results in a quite complete picture of the environment above the soil and can help determine the suitability for planting the seeds.

The robot can also be used in predetermined areas. Forest fires[21], for example, increase the nitrogen in the soil and in most cases the amount of carbon is also increased. This results in a soil that is suitable and fertile enough to deploy our robot on.

Drilling/plowing/seeding mechanism

A thing to keep in mind is the cost-effectiveness of the planting method. this article analyses the usage of an auger against the usage of spades.[22] While the article concludes that spades are more cost-efficient, the easier development and the lower priority of manhours would still make the auger a better option for this project.

This article shows how direct seeding is viable and what parameters have effect.[23] Using the appropriate sensors to measure these parameters would greatly benefit the project.

A kinematic analyses of an auger system[24] can be of great help when developing the seeding system for this project.

Development of a mobile powered hole digger for orchard tree cultivation using a slider-crank feed mechanism[25] gives another example of the design of an auger design, which doesn't straight up work for this case but gives some insights and can be used in this design.

An auger experiences certain loads during drilling. A mechanical analysis of the auger[26] could help in selecting the right parts for the job. This analysis has been done for bigger scale work on the moon, but is still relevant due to the use of variables which can be evaluated for their earth counterpart.

Reforestation and Forest Fires

Fires in the Yellowstone National Park cause burn severities around the Park. Fires of different sizes cause different ecological responses. The location of the fire has the biggest influence on the biotic response of the ecosystem. Severely burned areas mainly know pine seedlings while having less vascular species than before the fire. The bigger the burned down area, the more tree seedlings sprout, and the lower the general species diversity is. (Turner, M.G. et al. 1997) [27]

In recent years a lot of deforestation has occured in Latin America and the Caribbean. But a lot of forest recovery has also sprouted, partly caused by demographic and socio-economic change. This is the main factor influencing change in wood growth. Woody vegetation change was dominated by deforestation in 2001-2010 (-542 thousand km^2), but 362 thousand km^2 was recovered. As woody vegetation depends so heavily on deforestation and reforestation these need to be controlled more extensively. (Aide, T.M. et al. 2013) [28]

Current deforestation and combat methods

Deforestation is clearing Earth’s forests on a massive scale, often resulting in damage to the quality of land. The world’s rain forests could completely vanish in a hundred years at current rate of deforestation. Consequences of deforestation are the loss of habitat for millions of species and climate changes. The most feasible solution to deforestation is to carefully manage forest resources by eliminating clear-cutting to make sure forest environments remain intact. The cutting that does occur should be balanced by planting young trees to replace older trees felled. The number of new tree plantations is growing each year, but their total still equals a tiny fraction of the Earth’s forested land. (Geographic, 2015) [29]

Rehabilitation of deforestation areas can have different steps. It can include anti-erosion works, projects for slope formation and protection and reforestation. The prototype will focus on reforestation. The forest service takes into account the type of vegetation that has been burned, the success potential of natural regeneration of trees and the general conditions, and, accordingly, shall proceed, or not, to artificial reforestation of burnt areas using native species. The purpose of reforestation is the creation of new forests, the renewal of mature forests and the recovery of degraded forest ecosystems while ensuring natural regeneration or artificial intervention (seeding or planting) for production purposes and the protection of soils. The cost of reforestation in the last 8 years was enormous due to many manhours. (Christopoulou, 2011) [30]

This website reviews many different ways for reforestation. Almost all methods are based on man work, people are physically present and are planting the seeds themselves: direct seeding. One method that is currently used that does not involve a person physically being where the seed is planted is called aerial seeding. This method plants new seeds using planes and helicopters. This method is much more efficient than being physically present on the ground but is generally outside the budget of most reforestation projects. (David, 2015)[31]

Seeds of different species have different optimal depths for sowing, with some growing best if they are buried a few inches deep in the soil, while others, including many grasses and herbs, need exposure to light to germinate and so need to be on the surface. A rule of thumb when growing vegetables and grains is to sow the seed at a depth of one to two times the width of the seed. If seeds of one species, or a mixture of seeds of different species with different needs are randomly mixed in a larger seed ball, at least some of the seeds should be in the optimal position for germination. This optimizes reforestation. (Goosem & Tucker, 2013)[32]

Current use of Robotics Technology in seeding/reforestation activities

The use of machinery in agriculture, the logging industry and nature upkeep is commonplace, however the application of autonomous robotic technology is still rather in its infancy. Some robotics solutions exist in these field, which are primarily categorised in 2 classes: a mobile robotic class and a drone class. Examples in the mobile robotic class include the R-Stepps project to combat desertification (Mohamed, Flavien & Pierre, 2015) [33] and the Agribot to plant seeds on farming land (Pavan et al., 2017) [34]. Examples in the drone class include the Treek'lam (Sinalkar & Phade, 2016) [35] and

Project pages

For all the branches of the project diverging from the literature review, please see their respective pages

Bibliography

  1. ↑ 1.0 1.1 Farritor, S. & Dubowsky, S.. Autonomous Robots (2001) Volume 10, pp57-65. “On Modular Design of Field Robotic Systems”. https://doi.org/10.1023/A:1026596403167
  2. ↑ Bawden, O., Ball, D., Kulk, J., Perez, T., & Russell, R.. Australian Conference on Robotics and Automation (2014). “A lightweight, modular robotic vehicle for the sustainable intensification of agriculture.”
  3. ↑ Bak, T., & Jakobsen, H.. Biosystems Engineering (2004), Volume 87, pp 125-136. "Agricultural robotic platform with four wheel steering for weed detection.". https://doi.org/10.1016/j.biosystemseng.2003.10.009
  4. ↑ Li, G., Urbina, R., Zhang, H., & Gomez, J. G.. International Conference on Advanced Mechatronic Systems (ICAMechS) (2017), pp 145-150. “Concept design and simulation of a water proofing modular robot for amphibious locomotion.”. IEEE. https://doi.org/10.1109/ICAMechS.2017.8316566
  5. ↑ Cordes, F., Bindel, D., Lange, C., & Kirchner, F.. Proceedings of the 10th International Symposium on Artificial Intelligence, Robotics and Automation in Space (iSAIRAS’10) (2010), pp. 38-45. “Towards a modular reconfigurable heterogenous multi-robot exploration system.”
  6. ↑ Unsal, C., Kiliccote, H., & Khosla, P. K. (1999, August). “I (CES)-cubes: a modular self-reconfigurable bipartite robotic system.”. In Sensor Fusion and Decentralized Control in Robotic Systems II (Vol. 3839, pp. 258-270). International Society for Optics and Photonics. https://doi.org/10.1117/12.360346
  7. ↑ Murata, S., Yoshida, E., Kamimura, A., Kurokawa, H., Tomita, K., & Kokaji, S. (2002). “M-TRAN: Self-reconfigurable modular robotic system.” IEEE/ASME transactions on mechatronics, Volume 7, pp431-441. https://doi.org/10.1109/TMECH.2002.806220
  8. ↑ Jorgensen, M. W., Ostergaard, E. H., & Lund, H. H. (2004, September). “Modular ATRON: Modules for a self-reconfigurable robot.”. Intelligent Robots and Systems, 2004.(IROS 2004). Proceedings. 2004 IEEE/RSJ International Conference on (Vol. 2, pp. 2068-2073). IEEE. https://doi.org/10.1109/IROS.2004.1389702
  9. ↑ Baca, J., Hossain, S. G. M., Dasgupta, P., Nelson, C. A., & Dutta, A. (2014). “Modred: Hardware design and reconfiguration planning for a high dexterity modular self-reconfigurable robot for extra-terrestrial exploration.” Robotics and Autonomous Systems, Volume 62, pp 1002-1015. https://doi.org/10.1016/j.robot.2013.08.008
  10. ↑ Yim, M., Roufas, K., Duff, D., Zhang, Y., Eldershaw, C., & Homans, S. (2003). “Modular reconfigurable robots in space applications.”. Autonomous Robots, Volume 14, pp 225-237. https://doi.org/10.1023/A:1022287820808
  11. ↑ Hashimoto et al. (1996). United States Patent 5554980 Retrieved from: https://patentimages.storage.googleapis.com/eb/4b/ce/ba560b94ae5c1a/US5554980.pdf
  12. ↑ Kessler, A.M. (2015) Elon Musk Says Self-Driving Tesla Cars Will Be in the U.S. by Summer, Retrieved from: http://www.oharas.com/ET/elonmusk.pdf
  13. ↑ Matsushiro. (1984). United States Patent 4457101 Retrieved from: https://patentimages.storage.googleapis.com/14/b4/e5/e0e06d46e4cf44/US4457101.pdf
  14. ↑ Bagloee, S.A. et al. (2016). Autonomous vehicles: challenges, oppurtunities and future implications for transportation policies. Journal of Modern Transportation, Vol 24, Issue 4, page 283-303 section 6 Retrieved from: https://link.springer.com/article/10.1007%2Fs40534-016-0117-3
  15. ↑ http://www.instructables.com/id/How-to-Dynamically-control-a-servo-or-motor-throug/
  16. ↑ Jameco Electronics, Retrieved from: https://www.jameco.com/jameco/workshop/howitworks/how-servo-motors-work.html
  17. ↑ https://www.tinytronics.nl/shop/nl
  18. ↑ Edward M. Barnes, Kenneth A. Sudduth, John W. Hummel, Scott M. Lesch, Dennis L. Corwin, Chenghai Yang, Craig S.T. Daughtry, and Walter C. Bausch, “Remote- and Ground-Based Sensor Techniques to Map Soil Properties”, http://www.ingentaconnect.com/content/asprs/pers/2003/00000069/00000006/art00002#
  19. ↑ Boyan Kuang, “On-line Measurement of Some Selected Soil Properties for Controlled Input Crop Management Systems” (2012), https://dspace.lib.cranfield.ac.uk/bitstream/handle/1826/7939/Boyan_Kuang_Thesis_2012.pdf?sequence=1&isAllowed=y
  20. ↑ Sandra F. H. Correia, Paulo Antunes, Edison Pecoraro, Patrícia P. Lima, Humberto Varum, Luis D. Carlos, Rute A. S. Ferreira, and Paulo S. André, “Optical Fiber Relative Humidity Sensor Based on a FBG with a Di-Ureasil Coating” (2012), http://www.mdpi.com/1424-8220/12/7/8847
  21. ↑ L.M. Zavara, R. De Celis, A. Jordán, “How wildfires affect soil properties. A brief review”(2014), https://dialnet.unirioja.es/descarga/articulo/4847440.pdf
  22. ↑ Preece, N. D., van Oosterzee, P., & Lawes, M. J. (2013). Planting methods matter for cost-effective rainforest restoration. Ecological Management and Restoration, 14(1), 63-66. doi:10.1111/emr.12017
  23. ↑ Atondo-Bueno, E. J., López-Barrera, F., Bonilla-Moheno, M., Williams-Linera, G., & Ramírez-Marcial, N. (2016). Direct seeding of oreomunnea mexicana, a threatened tree species from southeastern mexico. New Forests, 47(6), 845-860. doi:10.1007/s11056-016-9548-2
  24. ↑ Bogdanof, G. C., Moise, V., Visan, A. L., & Ciobanu, G. V. (2017). Kinematic analysis of soil drilling mechanism used in afforestation. Paper presented at the Engineering for Rural Development, , 16 653-658. doi:10.22616/ERDev2017.16.N131 Retrieved from www.scopus.com
  25. ↑ Zong, W. Y., Wang, J. L., Huang, X. M., Yu, D., Zhao, Y. B., & Graham, S. (2016). Development of a mobile powered hole digger for orchard tree cultivation using a slider-crank feed mechanism. International Journal of Agricultural and Biological Engineering, 9(3), 48-56. doi:10.3965/j.ijabe.20160903.1784
  26. ↑ Cheng, Wei & Wang, Hongliu & Liu, Tianxi. (2013). Mechanical model of hollow-external-screw drill rod for lunar soil particle vertical conveying. IEEE International Conference on Control and Automation, ICCA. 1240-1245. 10.1109/ICCA.2013.6565063.
  27. ↑ Turner, M.G. et al. (1997). Effects of fire size and pattern on early succession in Yellowstone National Park, Ecological Monographs 67(4) pp. 411-433 Retrieved from: https://doi.org/10.1890/0012-9615(1997)067[0411:EOFSAP]2.0.CO;2
  28. ↑ Aide, T.M. et al. (2013), Deforestation and Reforestation of Latin America and the Caribbean (2001-2010) BIOTROPICA 45(2): 262-271 Retrieved from: 10.1111/j.1744-7429.2012.00908.x
  29. ↑ National Geographic. (2015, April). Deforestation. Retrieved from National Geographic: https://www.nationalgeographic.com/environment/global-warming/deforestation/
  30. ↑ Christopoulou, O. (2011). Deforestation/ reforestation in Mediterranean Europe: The Case of Greece. Soil Erosion Studies, 3-30.
  31. ↑ David. (2015, January ). Reforestation Methods Reforestation Projects. Retrieved from Reforestation: https://reforestation.me/reforestation-methods/
  32. ↑ Goosem, S., & Tucker, N. (2013). Repairing the Rainforest . Cairns: Wet Tropics Management Authority and Biotropica Australia Pty.
  33. ↑ Mohamed, Z., Flavien, V., & Pierre, B. (2015, October). Mobile robotics for restoring degraded ecosystems. In Global Humanitarian Technology Conference (GHTC), 2015 IEEE (pp. 273-278). IEEE. https://doi.org/10.1109/GHTC.2015.7343984
  34. ↑ Pavan, T. V., Suresh, R., Prakash, K. R., & Mallikarjuna, C. (2017). Design and Development of Agribot for Seeding.
  35. ↑ Sinalkar, S., & Phade, G. (2016, December). Treek'lam. In Global Trends in Signal Processing, Information Computing and Communication (ICGTSPICC), 2016 International Conference on (pp. 611-614). IEEE. https://doi.org/10.1109/ICGTSPICC.2016.7955373
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