Introduction: Train Wild Birds to Exchange Litter for Food!
I have trained wild magpies in my garden to trade litter for food !
The whole project relies on mechanical design, electronics, software and the great opportunity to create a machine with parts from my 3D-printer. I have worked with this project to and from for several years, but now in recent months the project has had an exciting development, and as I write in the title... Now the magpies work as garbage collectors, payed with food!
The food dispenser, must be: Fully autonomous,remote AND reliable
I work everyday with industrial applications of artificial intelligence (AI)... so the whole rig for the magpie project must be:
- Autonomous- Reliable- Flexible- Completely remote controlled- Document and log data and video.
I spent remarkably much time creating the actual food dispenser.
After testing with several Thingiverse designs of pet feeders, often based on a rotating feeder screw, I left these techniques. The dispenser must never get stuck and I want to be able to feed out individual peanuts. I looked at industrial solutions and got hooked on vibrating feeders. The base of the feeder is a fantastic vibration feeder from thingiverse. https://www.thingiverse.com/thing:2118961
Choose ABS or PETG for the four 'dog-bone' parts, PLA does not last long.
To this design I have added a number of extensions and funnels, I upload these as STL files. But, these are quick and dirty designs, you have to attach the parts on your own with small sheet-metal sheets, or in another way. Sorry for this, but when I build I am often experimenting and usually don't know exactly what the solution will look like... My parts to extend the vibro feeder can be found here:https://www.thingiverse.com/thing:4601125
One of these funnel parts has a 5mm socket for IR-LED and photodiode. with this arrangement I can run the dispenser with increasing intensity until I detect a peanut, Then stop the vibrating motor.
The vibrating motor is a simple 4.5 v DC motor. I made an unbalanced flywheel to this motor, included here https://www.thingiverse.com/thing:4601125 as STL The BirdBox is controlled by a Raspberry Pi 4 with an add-on board. The add-on board includes a DC motor controller.
There is also two arduinos in the design. For the raspberry, there is a python program that is controlling the logic of the feeder. I use the VNC feature together with AnyDesk to have full access to the BirdBox from 'remote'. The python code incorporates a simple GUI where I can see and log the progress and status of the BirdBox.
Supplies
Raspberry Pi 4
Wideangle picam
Arduino , preferable with 3.3 v logic.
Adafruit fetaher (arduino)
Step 1: The Food Dispenser, Must Be: Fully Autonomous,remote AND Reliable
I work everyday with industrial applications of artificial intelligence (AI)... so the whole rig for the magpie project must be: - Autonomous- Reliable- Flexible- Completely remote controlled- Document and log data and video.
I spent remarkably much time creating the actual food dispenser. After testing with several Thingiverse designs of pet feeders, often based on a rotating feeder screw, I left these techniques. The dispenser must never get stuck and I want to be able to feed out individual peanuts. I looked at industrial solutions and got hooked on vibrating feeders. The base of the feeder is a fantastic vibration feeder from thingiverse. https://www.thingiverse.com/thing:2118961 Choose ABS or PETG for the four 'dog-bone' parts, PLA does not last long. To this design I have added a number of extensions and funnels, I upload these as STL files. But, these are quick and dirty designs, you have to attach the parts on your own with small sheet-metal sheets, or in another way. Sorry for this, but when I build I am often experimenting and usually don't know exactly what the solution will look like... My parts to extend the vibro feeder can be found here:https://www.thingiverse.com/thing:4601125 One of these funnel parts has a 5mm socket for IR-LED and photodiode. with this arrangement I can run the dispenser with increasing intensity until I detect a peanut, Then stop the vibrating motor. The vibrating motor is a simple 4.5 v DC motor. I made an unbalanced flywheel to this motor, included herehttps://www.thingiverse.com/thing:4601125 as STL The BirdBox is controlled by a Raspberry Pi 4 with an add-on board. The add-on board includes a DC motor controller. There is also two arduinos in the design. For the raspberry, there is a python program that is controlling the logic of the feeder. I use the VNC feature together with AnyDesk to have full access to the BirdBox from 'remote'. The python code incorporates a simple GUI where I can see and log the progress and status of the BirdBox.
The project has been running for several years. The video-clips you see on this page is the result of stubborn work and several steps. Step 1 is to make the birds interested and familiar with the feeder. I recommend anyone interested in setting up similar experiments to start with that. You need to feed the birds regularly to get your 'site' included in their 'patrol-scheme'. That is why I start to publish designs necessary for this initial phase. The feeder, and some sort of experiment site, like the general food-bowl included in the STL files.
Step 2: Detecting and Classifying the Bottlecaps
The bottle-caps are detected and 'accepted' with a dedicated 3D-printed metal-detector based on some arduino code. I have created a simple GUI for the raspberry, with this GUI, Anydesk, and a wide angle Picam attached to the Raspberry monitoring the experiments. This has been very valuable since I have had to run the experiments fully autonomous, setting up an experiment, going to work, and then follow up the result later that day. I will describe the electronics and software later on this page... History of the project, and how I trained the magpies.
Today. 2020-10-17, I uploaded a YouTube video describing how I trained the birds !
Step 3: Next Steps...
I'd love to share this project and my experiences with everyone interested. What could come out from similar experiments when a large community get engaged? I work intense right now to prepare my project files etc for sharing...more to come.
The next planned step step involves an attempt to get the birds to collect 'fallen-fruit' in my garden. Are apples to heavy ? In the longer run, I think it would be possible to train for almost anything. Bottle-caps was relatively easy to 'classify' with a metal-detector. Other items, such as cigarette-butts, 'candy-paper', slugs etc will require a more general method for classifying. Fortunately I spend my days with applied AI and machine-learning.In my profession, we build smart sensors based on small & fast neural-networks such as mobile-net and YOLO. It is fully feasible to run such networks on small platforms such as the RPI 4. This could be the foundation of a general classifying method for a system like the BirdBox.
