• Engineers design autonomous robot that c

    From ScienceDaily@1:317/3 to All on Tue Nov 9 21:30:36 2021
    Engineers design autonomous robot that can open doors, find wall outlet
    to recharge

    Date:
    November 9, 2021
    Source:
    University of Cincinnati
    Summary:
    Engineering students have designed an autonomous robot that can
    find and open doors in 3D digital simulations. Now they're building
    the hardware for an autonomous robot that not only can open its
    own doors but also can find the nearest electric wall outlet to
    recharge without human help.



    FULL STORY ==========================================================================
    One flaw in the notion that robots will take over the world is that the
    world is full of doors.


    ==========================================================================
    And doors are kryptonite to robots, said Ou Ma, an aerospace engineering professor at the University of Cincinnati.

    "Robots can do many things, but if you want one to open a door by itself
    and go through the doorway, that's a tremendous challenge," Ma said.

    Students in UC's Intelligent Robotics and Autonomous Systems
    Laboratory have solved this complex problem in three-dimensional digital simulations. Now they're building an autonomous robot that not only can
    open its own doors but also can find the nearest electric wall outlet
    to recharge without human assistance.

    This simple advance in independence represents a huge leap forward
    for helper robots that vacuum and disinfect office buildings, airports
    and hospitals.

    Helper robots are part of a $27 billion robotics industry, which includes manufacturing and automation.

    The study was published in the journal IEEE Access.

    UC College of Engineering and Applied Science doctoral student Yufeng
    Sun, the study's lead author, said some researchers have addressed the
    problem by scanning an entire room to create a 3D digital model so the
    robot can locate a door. But that is a time-consuming custom solution
    that works only for the particular room that is scanned.



    ==========================================================================
    Sun said developing an autonomous robot to open a door for itself poses
    several challenges.

    Doors come in different colors and sizes with different handles that might
    be slightly higher or lower. Robots have to know how much force to use
    to open doors to overcome resistance. Most public doors are self-closing,
    which means if the robot loses its grip, it has to start over.

    Since UC students are using machine learning, the robot has to "teach"
    itself how to open a door, essentially through trial and error. This
    can be time- consuming initially, but the robot corrects its mistakes
    as it goes.

    Simulations help the robot prepare for the actual task, Sun said.

    "The robot needs sufficient data or 'experiences' to help train it,"
    Sun said.

    "This is a big challenge for other robotic applications using AI-based approaches for accomplishing real-world tasks." Now, Sun and UC master's student Sam King are converting Sun's successful simulation study into
    a real robot.



    ==========================================================================
    "The challenge is how to transfer this learned control policy from
    simulation to reality, often referred to as a 'Sim2Real' problem,"
    Sun said.

    Digital simulations typically are only 60% to 70% successful in initial
    real- world applications, Sun said. He expects to spend a year or more
    bridging the gap to perfect his new autonomous robotics system.

    So there's plenty of time to invest in robot-proof door locks.

    Video of a robot that can open a door:
    https://www.youtube.com/ watch?v=O_FV47hIRus ========================================================================== Story Source: Materials provided by University_of_Cincinnati. Original
    written by Michael Miller. Note: Content may be edited for style and
    length.


    ========================================================================== Journal Reference:
    1. Yufeng Sun, Lin Zhang, Ou Ma. Force-Vision Sensor Fusion Improves
    Learning-Based Approach for Self-Closing Door Pulling. IEEE Access,
    2021; 9: 137188 DOI: 10.1109/ACCESS.2021.3118594 ==========================================================================

    Link to news story: https://www.sciencedaily.com/releases/2021/11/211109193246.htm

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