[D] Development challenges of an autonomous gardening robot using object detection and mapping.

Submitted by science-raven t3_11oaek2 in MachineLearning

Why do some folk think that this futuristic type of robot can't logically achieve a broad array of stated ML tasks?

https://youtu.be/EYTiTh7_zO4

I see the dev cost of this robot as being 100 times less than a self-driving car: single error fatality risk, unlimited chaotic cities, 90mph compute time limits, make self-driving cars unfeasible compared to multitask garden robots.

Fruit-picking is very difficult using AI, but weeding, digging, sowing seeds, irrigation, are fairly easy tasks, and an experienced developer knows that anything is possible with logic.

Millions of acres of farmland are chemically and brutally treated for food that is wrapped in plastic, shipped hundreds of miles, to supermarkets, so as an environmental chemist, rural processes analyst and EE dabbler, I have created an emulator prototype for a garden robot :)

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MrTacobeans t1_jbs7jtu wrote

I think the biggest issue here though is a large part of a bot like this would be traditional programming. The type of AI hardware needed for these tasks in the garden would likely eclipse the bots 3k goal for the foreseeable future.

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science-raven OP t1_jbsbbyz wrote

Nvidia Jetson Nano and Raspberry Pi can run 2 FPS of AI object detection, on Yolo NN code. A Yolo model can differentiate 80 different objects, and you can run 20-50 different Yolo models, to detect 10,000 different objects.

The traditional programming copies the AI identification objects to a 3D map of the zone.

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Real_Revenue_4741 t1_jbteqca wrote

YOLO is not enough to create these robots. The difficult part of robotics is being able to actuate from visual feedback. The method you are mentioning is called "visual servoing," and will not be robust enough to actually work. Also, the under 3K price point is quite a bit lower than what you would expect for these projects.

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science-raven OP t1_jbtzsn5 wrote

Thanks for the info. The robot has an onboard map of the entire garden which is accurate to a couple of inches and an ultrasound ping, so it can arrive anywhere without processing.

I found a visual servoing demo using a Raspberry Pi from 2015, and today the v4 is four times faster than that. How can it fail at accurate placement when all the objects in the garden are static, and it has limitless time for processing the most difficult tasks?

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MrTacobeans t1_jbu7nw4 wrote

Regardless of the possibilities of this being possible this robot even at economies of scale looks more like 15-20k. Advanced lawn roombas are already in the 2-5k range a fully autonomous lawn/garden maintenance bot will never be below 5k... Unless it's just running around spraying water on stuff. The arm in your video alone would likely cost atleast 2-3k after R&D is factored in

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science-raven OP t1_jbwl03o wrote

Fixed variable cost analysis is crucial. 15k is very high. If you put 10 skilled workers on it for a year, plus development labs, it would cost about $1.2 million, including outsourcing to specialist engineers to refine the CAD files.

At high volumes, like 4000 units, that is divided to $300 RnD per unit. Obviously, it would benefit from a 2-3 million dev budget though.

The bill of materials is 3000, The metal welding is $500 and the assembly is another 500, so an open source kit would be less than 4000 dollars, and a fully built kit would also be 5000.

Husqvarna and roomba companies sell by market price, not the production price, so they can markup a high value, and they use custom circuit boards, custom plastic moulds including big thermoplastic pieces.

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Real_Revenue_4741 t1_jbuhm8y wrote

In essence, "interacting with an object with an end effector" requires a lot of precision. It is more difficult than it seems to get it working on all types of weeds/plants. Weeding/digging requires a specific motion that may be difficult to accomplish without tactile feedback--it is not as simple as putting the tool at the right location. Irrigation may be easier because there is not much interaction with the environment required. It will be pretty simple to get a system that works with suboptimal performance, but this would be not be enough to automate gardening without human intervention.

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science-raven OP t1_jbvlacq wrote

There's two types of weeding, the most common is the huge quantities of seedlings that come up in new soil. That's dizzyingly easy for a human, and it's not too difficult for a robot. It's too repetitive for a human. The difficult types of weeds are those that have to be drilled, because humans don't have drills and mapping ability.

Drilling soil using an auger is actually a back and forth movement using just one vector on a single motor. The arm has at least 1 force sensor in the tool piece.

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deephugs t1_jbtqk9c wrote

The devil is in the details. Getting robots to work reliably in the gritty dirty environments of agtech is incredibly difficult. Manipulation, even with modern ML and CV, is still very difficult. Let's just say there is a reason there aren't a ton of robotics companies selling a product such as the one you suggested.

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science-raven OP t1_jbu4m9q wrote

If you spend a moment on YT to see the latest projects, there are quadcopters that pick apples, and many awesome fruit picking demonstrations. AI is fanning out into many fields.

Technologies can come late because they have been missed: electronic cigarettes could have existed since the 1930's when propylene glycol was used for medicines.

For the grit, yes it's tricky, the robot can ask for a brush down every week, there can be teflon coatings, agri-alloys, a brush so the robot can tidy tools, a stethoscope audio sensor.

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optorobotics t1_jc24knt wrote

seriously, how much would you pay if such a robot exist say can do weeding, digging, sowing seeds, irrigation. Would you buy it?

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