P3: Sortable Recycling System
Project Overview:
A major issue that exists is that over 30 percent of items but in recycling bins are not recyclable. In this project, our team was tasked with creating a mechanism and a computer program to automate the job of recycling by sorting containers using a robotic arm, colored bins, and a terrestrial based land vehicle. In order to sort each object, attributes such as weight and material needed to be detected. To achieve the goal of sorting, the team was split into the following sub-teams:
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- Computing (Writing algorithm for the q-bot, q-arm, material detection, etc)
- Modelling (Creating mechanism for hopper to drop containers into bin)
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In this project, I was assigned to the computing sub-team.
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Objectives:
1) Accurately Identify Different Recyclable Containers:
Method of identifying each container must be created to ensure each container is accurately sorted
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2) Simple & Reliable Mechanisms
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Mechanism to dispense each container must be simple and effective to reduce mechanical errors/issues
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3) Use of a computer program to automate the process
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Algorithm must be created to facilitate the sorting of containers automatically without the use of human intervention
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To achieve these objectives, our sub-team (computing) came up with a modular program that efficiently and effectively sorts each container based on predetermined attributes such as material, weight, and color.
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Python program to faciltate sorting
Simulated Sorting Environment
Skills:
Use of Python to create the final program which controls the Q-bot, Q-arm, and contains the algorithms for line following, bin detection, and container dispensing.
Reflection:
As the primary computing member on the computing sub-team, it was my job to oversee and decide on how the main computer program which facilitated the sorting system was created. This involved planning the algorithms for areas such as the line following, color detection, etc. While working on the computing part of the project, I came across various challenges and obstacles that forced me to reconsider and learn different approaches on how to implement a proposed solution. The line following algorithm was especially difficult to implement as the sensors on the q-bot in the virtual environment were providing faulty sensor data. It took a lot of analysis and questioning to realize that the issue was the fact that the segment of the program that set the wheel speed did not have enough time in the program to adjust the position of the q-bot on the line before the code loop continued. The solution was as simple as adding delays in key segments and adjusting the wheel speed settings. These challenges made me consider the importance of testing and refining during the prototyping phase, and how issues that occur during this phase can highlight key oversights made by the design team. In conclusion, this project was instrumental in increasing my understanding of computing/programming and finding ways to implement solutions effectively.