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\title{Walk-E - Servo actuated walking robot}
\author{A project in IN5590 by Robert Saunderson E-mail: roberasa@ifi.uio.no }

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        \section{Intro}
        The goal of this project was to challenge and expand my skills in computer aided design (CAD) and 3D-printing with a focus towards prototyping robotic systems. I chose to work on a bipedal walking robot. Inspired by an earlier assignment in the course on strength testing 3D-printed designs, I chose to only use 3D-printed material for the structural elements of the robot and use generative design to maximize strength and minimize the weight of each part. In short, the original goals of the project were: 
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            \item Create a bipedal robot design that can traverse both smooth and rough terrain
            \item Attempt to use 3D printing for structural parts
            \item Gain experience with Dynamixel servos for robotics
            \item Develop a versatile platform to gain experience with programming robotic systems
            \item Possibly implement control theory and learning algorithms to optimize movement
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        \section{Tools}
        The most important tool used for this project was Solid Works CAD software with it's built in topographical study software (generative design) used to inspire the design of the limbs. Other than this, the project used:
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            \item 2x Dynamixel AX12 (knee joints)
            \item 2x Dynamixel AX18 (Hip joints)
            \item PLA filament
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        The software for Walk-E is a python script that generates messages to the Dynamixel servos.

        \section{Conclusion}

        The project is considered a success in terms of achieving the primary goals. The 3D-printed parts are stronger than expected and quite light. This means that the topographical study in Solid Works was a useful tool to optimize strength and weight. The goals to walk on different terrain and to use control theory and learning algorithms became too ambitious for my experience in those topics and the time available for the project.

        Future improvements to this project would be testing it on different terrain and possibly implementing a learning algorithm. More work could in general be done in fine tuning the walking algorithm. In terms of topographical study, comparing results from different topographical study tools would be interesting to explore, as the only tool tested in this project was Solid Works's built in tool.
    
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