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    A soft robot capable of simultaneously grasping an object while navigating around an environment

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    License
    Attribution 4.0 International
    Date Issued
    2019
    Author(s)
    Yin, Alexander Heng-Yu
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    Embargoed until:
    2021-06-03
    Permanent Link
    https://hdl.handle.net/2144/36032
    Abstract
    In recent years, the field of Soft Robotics has grown exponentially resulting in a variety of different soft robot designs. A majority of the current soft robots can easily be split into two distinct categories: Navigation and Grasping. Navigation robots alter their body orientation to navigate around an environment. Grasping robots are designed to grasp a variety of unknown objects without damaging said object. However, only a few robots are able to demonstrate both aspects and even fewer robots are able to do both simultaneously. As thus, the goal of this thesis is to create a soft robot that is able to pick up and support an additional payload. This thesis will explore the challenges and difficulties that come with designing such a robot. For this thesis, we chose to simplify the manufacturing process making it easy to create and test different designs. We primarily used Pneumatic Network actuators for the majority of the soft robot. This allowed us to use a layered manufacturing approach to create the full robot. Finally, we split the robot into two main components which have their own purpose, which made it easy to test and design each component. Attached to this thesis are three different supplementary videos. The first one labeled "Walking Gaits" demonstrate how the robot is capable of moving forward. This video is comprised of several sections showing the full robot moving, just the base moving, and the full robot briefly moving as it supports a payload. The second video is labeled "Additional Walking". This video shows how the base can effectively move around a given environment. The final video if called "Grasping Method" which demonstrates the different grasping methods that the full robot uses to pick up objects.
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    Attribution 4.0 International
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    • Boston University Theses & Dissertations [6905]


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