PRE2015 4 Groep2

(Wiki markup cheatsheet)

Group 2 members

• Cameron Weibel (0883114)
• Maarten Visscher (0888263)
• Raomi van Rozendaal (0842742)
• Birgit van der Stigchel (0855323)
• Mark de Jong (0896731)
• Yannick Augustijn (0856560)

Project ideas

Agritech automation

Links about agritech:

MIT Food Computer: https://www.youtube.com/watch?v=LEx6K4P4GJc

Dickson Despommier on the vertical farm: https://www.youtube.com/watch?v=XIdP00u2KRA

Agriculture is the fastest growing robotic sector: http://www.eetimes.com/document.asp?doc_id=1329273

Japanese firm to open world’s first robot-run farm: http://www.theguardian.com/environment/2016/feb/01/japanese-firm-to-open-worlds-first-robot-run-farm

Aeroponics (we most likely won’t use this as an irrigation method): https://en.wikipedia.org/wiki/Aeroponics

Polyculture: https://en.wikipedia.org/wiki/Polyculture

Why to avoid monoculture: http://evolution.berkeley.edu/evolibrary/article/agriculture_02

LED lights for imitating sunlight: http://www.gereports.com/post/105532612260/the-future-of-agriculture-indoor-farms-powered-by/

Amigo sandwich baker

Make Amigo able to make sandwiches.

Standalone sandwich baker

Create a new device that is meant purely for creating sandwiches in Subway style (i.e. with ingredient picker).

Literature

• Yamamoto, S., et al. "Development of a stationary robotic strawberry harvester with picking mechanism that approaches target fruit from below (Part 1)-Development of the end-effector." Journal of the Japanese Society of Agricultural Machinery 71.6 (2009): 71-78. Link

• Sam Corbett-Davies , Tom Botterill , Richard Green , Valerie Saxton, An expert system for automatically pruning vines, Proceedings of the 27th Conference on Image and Vision Computing New Zealand, November 26-28, 2012, Dunedin, New Zealand Link

• Hayashi, Shigehiko, Katsunobu Ganno, Yukitsugu Ishii, and Itsuo Tanaka. "Robotic Harvesting System for Eggplants." JARQ Japan Agricultural Research Quarterly: JARQ 36.3 (2002): 163-68. Web. Link

• Blasco, J., N. Aleixos, and E. Moltó. "Machine Vision System for Automatic Quality Grading of Fruit." Biosystems Engineering 85.4 (2003): 415-23. Web. Link

• Cubero, Sergio, Nuria Aleixos, Enrique Moltó, Juan Gómez-Sanchis, and Jose Blasco. "Advances in Machine Vision Applications for Automatic Inspection and Quality Evaluation of Fruits and Vegetables." Food Bioprocess Technol Food and Bioprocess Technology 4.4 (2010): 487-504. Web. Link

State of the art

A small number of tests have been done with machines for harvesting strawberries. These are large, bulky and expensive machines like Agrobot. Cost prices are in the order of 50,000 dollar. Todo: add citations.

A lot of research is done towards inspection by means of machine vision. Todo: add citations and continue.

Further reading

• Agrobot video: https://youtu.be/RKT351pQHfI

Notes meeting 1

Goal: Create a demo in which a robotic system is able to detect ripe strawberries and harvest them effectively.

Subsystems: Robotic arm Machine Vision/Learning

Requirements for presentation: -USE needs (Yannick + Raomi Team Awesome) -Scientific literature -> EU projects -> How to go beyond? (Cameron) -Requirements --Moving to A to B along a fixed axis --Cutting fruit --Sensing for ripeness --Ambient sensing --Locating fruit --Collecting/Handling fruit effectively --Feedback from farmer to system

-Idea/Solution to the problem

--Moving to A to B along a fixed axis Fixed railing Cable Treads for conveying 4-wheel/2-wheel drive Yo-yo

--Cutting fruit Scissors Custom cutting mechanism Laser cutting Sharp knife (fruit ninja)

--Sensing for ripeness Kinect Color sensor pH sensor Force sensor Machine learning ripeness (with Kinect using training set of ripe fruit)

--Ambient sensing Temperature sensor Humidity Air pressure Sunlight exposure

--Locating fruit Kinect for depth map Probe for fruit (use color sensor to identify where fruit is located) Touch sense for fruit (and then use color sensor) Fixed location for fruit

--Collecting/Handling fruit effectively Basket collection Soft packaging Grip from stem

--Feedback from farmer to system

-Plan of approach Divide task into sub-groups: -Building the robotic arm (mechanical) (TB) -Machine Vision/Learning (software) (TC) -Control of the robotic arm (software and electronics) (TBC) -Feedback from farmer (software) (TA) -USE aspects (TA)

Key: TA: Yannick & Raomi TB: Mark & Maarten TC: Cameron and Birgit

Deadline Week1: Defining project plan and timeline Specify USE aspects and identify multiple solutions Elucidate requirements Compile Literature Create a presentation

Deadline Week2: First presentation Parts list (BOM) Order parts Begin drawings/concepts

Deadline Week3: Beginning of meetings Mark abandons us Consolidate drawings

Deadline Week4: Separately working components Working base for movement from A to B

Deadline Week5: Build the arm

Deadline Week6: Control of arm

Deadline Week7: Integration of subsystems

Deadline Week8: Testing of system Deadline Week9: Phase-out period