Introduction This is part two of a four-part series about autonomous navigation with ROS (Robot Operating System). In the previous blog post, I discussed the use of RTAB-mapping (real-time appearance-based mapping) in the self-driving vehicle. In this blog post, I will talk about how to plan out a path once we have a high definition…
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Introduction For the past two years, I have been researching and developing a self-driving golf cart. ROS (Robot Operating System) is an open source, robust, and convenient robotics middleware that I have for the golf cart. In this three-parts-series, I will discuss how I developed the golf cart’s autonomous navigation stack with ROS. There are…
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Introduction A self-driving vehicle requires a robust Drive-By-Wire (DBW) system. DBW allows the vehicle’s onboard computer to control the car’s motion using electrical signals. Most modern cars already come with a great electronics system. For example, you can even hack into a Toyota Camry and control the braking, throttle, and steering with open source software.…
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Introduction: For the past few months, I have been developing an all-new autonomous steering system for the self-driving golf cart. I not only developed a new deep learning model but also completely modified the hardware design. If you have been following my blog, you might have seen posts related to these topics. In this two-part…
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It has been a while since I published my last blog post. I am back! Life has been a little crazy lately. I am in the midst of my senior year in high school. Object Detection with YOLO When we talk about object detection, where are really two smaller tasks embedded in one larger task.…
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I have been developing a better end-to-end steering prediction system. Eventually, with a new architecture proposed by DeepMind, the software was able to achieve 0.0530 validation RMSE loss, which could land me among the top five teams for the Udacity self-driving challenge.
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Since the very beginning, Michael and I have been dedicated to contributing to the open source community. This Spring, we open sourced the entire repository for the self-driving golf cart project. In order to better host the code base, as well as to provide us with a platform for future research, we registered a Github…
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Want to learn more about self-driving car simulators? Check out this blog post. Simulators are crucial in developing a good self-driving system. Not everyone will have access to quality self-driving hardware platforms, therefore software simulator is a nature incubator for cutting-edge research and development.
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Introduction Convolutional neural networks are often known as “black boxes” for their mysterious nature. Unlike most programs that we write, computer scientist can’t directly modify the content (weights) of the neural networks to improve their performance. In order to create better machine learning models, you can either do a heck more training or experiments with…
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Introduction After our somewhat unsuccessful demo last Wednesday, my partner Michael Meng exclaimed, “there is no hope for deep learning”. The future is not that grim, but Michael is right to a certain degree. Deep learning has flaws and our deep learning powered self-driving golf cart certainly has lots of flaws. Today, I would like to…
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Neil Nie 