This project aims to increase the safety of large industrial garbage trucks when during reversing, specifically to avoid hitting people and objects. To achieve this a multifaceted sensing system is required to be mounted to the back of a truck, specifically consisting of 10 LiDAR sensors, 3 depth cameras, 1 visual (infrared) camera, a light sensor, an IMU, and a GPS sensor; all of which are controlled by 3 onboard microcontrollers, and 4 onboard mini compute units.

This is the culmination of my macro surface level aquatic trash cleaning robot; The Trashminator. Built for my tech design course, but evolved into a project with personal importance for me I am very happy with how it turned out. There are still improvements to be made, and I plan to continue working on it past the course culmination! The robot is able to autonomously navigate and clean up water bodies.

In this project, I complete a series of tasks involving the manipulation, cleansing, and analysis of a massive LIDAR point cloud. From removing anomalies to finding the two furthest points in a data set with millions of points, this project taught me some useful libraries and let me try some of my own algorithms and optimize their run time.

A fun group project we built as part of our mechatronics course. The robot sweeps an area and sorts bird eggs based on whether they are an invasive or protected species. The name Gooseminator arises from the fact that at Waterloo students often joke about how geese are invading and out of control.

In a year where everything was virtual this project was truly more than anything a test and development of my CAD skills. Using orthographic drawings over 20 intricate pieces had to be constructed and then assembled into a working linkage of a 6 cylinder radial engine. You can view animations and the CAD of the engine below.