I was reading the section in the book, “Thinking in Systems” about the tragedy of the commons and thought some of the recommendations might apply to software teams trying to manage their cloud infrastructure spending. When companies are young, they may optimize for development speed and flexibility and not focus on financial efficiency, This prioritization […]
In November of 2018, Amazon announced the launch of RoboMaker, a cloud robotics service that makes it easy to develop, simulate, and deploy robotics applications at scale. RoboMaker provides a robotics development environment for application development, a robotics simulation service to accelerate application testing, and a robotics fleet management service for remote application deployment, update, and […]
A friend of mine was asking me about the technical complexity of a children’s picture book reading robot, the Luka. The robot is used to read children’s books in both English and Chinese. It looks at the pages and then reads the book aloud in English or Chinese. This product has three primary requirements: Extracting […]
Below are some of my key takeaways from reading the book, Making Things Happen by Scott Berkun. If you are interested in more detailed notes from this book, they are available here.
This post describes my work setting up a mapping pipeline. I was initially inspired by Eric Theise’s presentation on creating a Geostak. However, the tutorial was from a few years ago and I had trouble setting up some of the applications on my Ubuntu 18.04 machine. I used this as an opportunity to leverage docker […]
The questions below are meant to be used in a guided discussion on the book, “Peopleware: Productive Teams and Projects” by Tom DeMarco and Timothy Lister. If you are interested in more detailed notes from this book, they are available here.
The purpose of this project was to develop a Machine Learning model to enable an RC car to autonomously navigate a race track using an Ouster OS1 lidar sensor as the primary sensor input. The model is an end-to-end Convolutional Neural Network (CNN) that processes intensity image data from the lidar and outputs a steering […]
Previously, the process for training and deploying an ML model to autonomously operate an RC car was described in the post, “RC Car End-to-end ML Model Development.” The purpose of the project was to develop an ML model that predicted steering angles given a color camera image input to enable the RC car to follow a […]
This post describes the process of developing a end-to-end Machine Learning model to steer an RC Car around using a color camera as an input. This is inspired by the Udacity Self Driving Car “behavior cloning” module as well as the DIY Robocars races. The purpose of this project is to create a pipeline for […]