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    Razor Robotic's Research

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    We are very active in the field of robotics and have a number of projects that we are currently researching. Our current research areas are detailed below:

    Safety of Human-Robot interaction

    Before personal robots can become reality, many safety issues need to be solved. Our research aims to investigate the following:
    • How can we test that no erroneous code will cause the robot to behave in an unsafe manner?
    • How can a robot identify what actions would be safe or unsafe?
    • How can we prove that a robot will behave safely?

    Example Problem: Robot Waiter

    Safety implications have always been a concern for robot designers and traditionally the solution has been to prevent the user coming into contact with the robot, by means of physical barriers. For personal robots to become a reality these barriers will need to be removed and more dynamic flexible safety methods introduced.

    For our research we are investigating the interdependencies between robot safety and robot control. This has led us to look at ways to better integrate the two processes and identify how safety can be designed to aid control routines. The following video shows an initial trial of our safety control system (details to be published soon).




    The next stage of our work will be to perform Human-Robot Experiments. The aim is to investigate the problem and determine whether humans should be treated as a special safety case and handled differently to other real world entities.

    Example Problem: Part Sorting Robot

    In addition to the diner environment we have explored other more structured domains. The part sorting robot operates in a semi-structured environment modelled on a warehouse.





    Click here to read more about Robot Safety »



    Face Recognition in Crowds

    Face recognition using existing CCTV technology Face recognition using existing CCTV technology
    Our research into reliable face-recognition seeks to answer the following:
    • Which is the best method for identifying an individual in a crowd?
    • Is is possible to identify individuals seeking to avoid face-recognition systems?
    • Can video footage of crowds taken from multiple angles be used to improve face-recognition reliability?









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