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Farming Automation

This page is to create a Road Map for Agricultural Farming Automation via 'Bots' and single board computers

Goals of Automation

  • Autonomous completion of tasks
  • Remote control (i.e. from Tiki site)
  • Swarm application (i.e. swarms in nature)
    • i.e. all drones connected (via code) and working as one unit in real time

Note: these are only long-term, macro goals which will take a substantial amount of time and steps to reach. As of early 2019, no commercial companies have achieved this, therefore the path is still wide open

Types of Automation Bots

  • Aerial Drones (Unmanned Aerial Vehicles, UAV's)
    • vertical, i.e. helicopters
    • horizontal, i.e. planes
  • Ground Bots
    • on wheels or tracks
    • on 'legs' i.e. spider
  • Fixed Bots
    • stationary or on a track
    • for small areas, i.e. small scale vegetable farming

Applications

Aerial drones

  • Applying crop protection (insecticides/ pesticides, herbicides, fertilizers, etc.) either:
    • only where necessary, i.e. herbicides, to reduce quantities sprayed, fertilizer according to where needed (per vegetation or soil maps), etc.
    • full field, i.e. pesticides, fertilizers, herbicides, etc.
    • current examples include a drone by DJI called Agras MG-1 and one by Kray Technologies
      • note issues they experienced by DJI with engines due to dust
  • Crop scouting (i.e. looking for problem areas in fields)
    • with mapping so results can be compared from year to year
    • First steps:
      • find similar open source code as the base for all future coding
      • focus on code that establishes communication and coordination between two drones to complete separate parts of one task, with the assumption that if one drone fails, the other can take over all tasks.
      • a starting task would be to fly over one agriculture field in straight lines using GPS while taking photos of each part of the field, than the photos would need to be combined into one (i.e. map) of the field. This will be a basis for all ariel drone operations, i.e. spraying crop protection, fertilizers, etc.
  • Vegetation Maps
    • provides a type of 'heat map' so that a map can be produced to determine health of a field
    • via infrared cameras (though expensive, from $10,000) and horizontal take off drones at a height of 300 - 1000m
  • Field perimeter boundaries
    • outlining and re-drawing field boundaries (via gps module)

Ground bots

  • Mechanical elimination of weeds (i.e. cutting)
    • can be designed like a lawn mower, as the width of rows is standard in commercial farming (from 30 - 70 cm)
    • but, can be very difficult as many times, the weeds grow in right up against the stem of the plant
  • Chemical elimination of weeds
    • similar to mechanical, in that a bot on wheels moves down a row (based on a field map 'A-B lines' + GPS) and individually sprays weeds, example here
    • this would solve the above issue of mechanical elimination of weeds when* the weed grows right up against the stem of the plant
  • Planting (with fertilizers)
    • a great application as there is almost no soil compaction (vs. a very heavy tractor + seeder + seeder tanks)

Single Board Computers

  • Connection between IoT devices and Tiki (Trackers)
    • Open Source computers, such as the Raspberry Pi and Arduino that will be used to connect drones, bots and other types of automation to Tiki Trackers for analyzing and graphically displaying data.
  • Other Applications
    • actuating servo motors and sensors - to turn applications on/ off, e.g. irrigation, fans, lights, etc.
    • cameras: time lapsed photography (crops), security, etc.
    • RFID Controllers: magnetic door locks, livestock monitoring

Open source code

  • There are many options for open source code which is compliant with drones, though many are more for serious enthusiasts (>$300) vs. the toy type drone market (<$300).

Drone Software Standards

  • Dronecode.org promotes standardization of OS drone software
    • "The Dronecode Project hosted under the Linux Foundation serves as the vendor-neutral home for PX4, MAVLink, QGroundControl, and the Dronecode SDK."
    • Links to all GitHub pages for development on this page, which include the Dronecode Project, Flight Stack, GCS, Coms, API's, Firmware/Hardware.

Flight Control Software

  • PX4 Autopilot - PX4 is an open source flight control software for drones and other unmanned vehicles.
  • Ardupilot.org is based on the Arduino single board computer, their site is well maintained and current.
    • "It is the only autopilot software capable of controlling any vehicle system imaginable, from conventional airplanes, multirotors, and helicopters, to boats and even submarines. And now being expanded to feature support for new emerging vehicle types such as quad-planes and compound helicopters."
    • their wiki is extremely detailed

Bots

  • Qualcom offers the 'Robotics RB3 Platform' - this makes starting easier (vs. 100% DIY). It "runs Linux with 'Robot Operating System (ROS)"..."Ubuntu suport is planned in the near future" (Feb. 2019)

Resources

  • DIYdrones.com is a strong source of information for all DIY drone projects
  • DroneGarageBlog is a good 'Open Source Drone Hardware and Software Reference'

Private Companies but Support Open Source

  • Auterion is the creator of PixHawk, MAVLink, QGC and PX4 and is currently the largest contributor to PX4 open source code.
  • Qualcomm - has been active in the drone market since 2015 promoting Linux on their boards
  • Hex (private company) is an "open source hardware manufacturer which produces open source drone autopilots" based on PixHawk which are accessible on their Download page
    • Link to an article on ArduPilot which demonstrates 'Zig-Zag' mode for piloting a drone back and forth across a field, e.g. crop spraying, which was done with the company listed above, Hex

Other Open Source Options

Other Open Source Tools

Drone Video Editing Tools

  • digiKam is an open source digital photo and video management application which is reported to support DJI drones
  • Blender is a leading open source tool
  • OpenShot is one more

Mapping

  • QGIS - A Free and Open Source Geographic Information System


Obstacles and Limitations

Artificial Intelligence (AI)

  • Autonomy: necessary for tasks and problems to be completed autonomously
  • Continual contact: contact between drones to work as one unit in real time
    • to be able to complete the task despite the loss of one or more drones
  • Resolving problems: numerous 'problems' will be encountered in the field on a daily basis, it will be necessary to create and prioritize these problems for developers to resolve such as:
    • evacuation and replacement when a drone breaks (power supply expires, environmental factors, like a tree falls on 10 - 20 planting bots), etc.)
    • re-programming remaining drones so task can be completed with remaining drones until the new one(s) arrive
    • visual recognition of problems
      • differentiating between the crops and weeds
      • differentiating problem areas of a field,, i.e. so additional liquid fertilizer can be applied only in those areas

Agriculture Environment

  • Agriculture is a very difficult working environment. Unlike, for example, an automobile factory, farming has:
    • a wide range of humidity, temperature and wind
    • significant dust, vibration, harshness
    • lack of easily accessible power
    • limited or no internet

Limitations of Drones / Bots

  • small farm bots cannot complete some farming operations such as 'Cultivation' and 'Harvesting' (see 'Sequence of Farming Operations ' at bottom of page)
    • Cultivation - will always require heavy equipment to dig into the ground, with one possible exception: no-till or low-till farming
    • Harvesting - combines are extremely complex pieces of equipment with thousands of moving parts, most likely it will not be economically possible to reproduce this on the scale of a small bot



Videos

Video by Dave Dorhout, presenting a planting bot called Prospero

  • set video to start at 1 min. 11 sec (before this it addresses the history of farming)
  • more about Prospero can be found on:
  • Why this project is interesting:
    • "Prospero is simple. Eschewing data-dense systems like GPS, Dorhout instead designed the Prospero bots to recall locations of seeds by simply talking to each other as they amble along. Following the model of ants, which mark places of interest (read: food) with pheromones so other ants can find them, he designed his 'bots to mark planted seeds with a shot of white spray paint that changes the reflectivity of the soil around the site. Other robots register this change in reflectivity, allowing them to see every seed in the field."

Sequence of Farming Operations

This is the order of steps, regardless of whether a planting season starts in spring or fall:

  1. Tillage - Plowing (very deep), Discing (deep), Cultivation (light), etc.
  2. Spraying - crop protection application (liquid)
  3. Planting - planting crops
  4. Fertilizing and Spraying (many times)- spreading (pellets) or spraying (liquid)
  5. Harvesting - gathering the crop



See also: http://wikisuite.org/Building


Created by Mike Finko. Last Modification: Thursday 21 March, 2019 21:58:11 GMT-0000 by Mike Finko.

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