BoxBot

BoxBot is a packaging robot that automatically produces a perfectly sized box for any package. By measuring each product and utilizing a packing algorithm, we are able to minimize cardboard waste.

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Inspiration

Every day, millions of packages are sent all over the world. However, we've noticed that many shipping companies use inefficient packaging to box their products. The amount of unnecessary space in each box amounts to a global average of 40% wasted, annoying customers and filling up more space in delivery trucks. If boxes are produced on-site with efficient box template cutting systems, we are able to fit more boxes into delivery trucks, while reducing the amount of cardboard used and the number of trucks sent out, reducing the industry's carbon footprint. Team B.A.D. took this as inspiration to create BoxBot.

What it does

The BoxBot measures the size of each shipping product and uses this to produce a cardboard template with an efficient packing algorithm. This template is then cut out from large rolls of cardboard, and folded into the optimal box for each item, accounting for fragile products as well. The excess cardboard is shredded and used for package fill for the fragile options.

How we built it

A model of BoxBox was produced with Python, using the pygame and customtkinter libraries. An app front was developed with customtkinter, which allows the user to input their product dimensions to a list. The user is able to select if the object is fragile or not, increasing the dimensions to account for packing material. Once the dimensions are added, a pygame window is used to show the best fit for each box template, using a packing algorithm.

Challenges we ran into

Some challenges we ran into included:

  • developing the algorithm was difficult, we had issues iterating through the list and drawing rectangles in the correct location
  • time constraints
  • difficulties in animation

Accomplishments that we're proud of

We were able to effectively produce an algorithm that packs each object efficiently into a window/cardboard sheet.

What we learned

We learned how to:

  • develop the best-fit algorithm
  • animate using fusion 360
  • use tkinter to make an app

What's next for BoxBot

We believe BoxBot or some other very similar idea will become widely adopted in the next couple of years by large shipping companies such as Amazon, who see the increased efficiency brought by this system. We would be cutting costs of cardboard, and gas usage, and reducing the industry's overall carbon footprint.

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