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  • 'Tell Me Dave' Robot From Cornell Could Become Your Smartest Servant

    Ankita Katdare

    Ankita Katdare

    @abrakadabra
    Updated: Jun 24, 2014
    Views: 1.7K
    Robotics enthusiasts all over the world are trying to build robots that understand your commands spoken in natural language and perform accordingly. The only drawback of using 'language parsing' techniques that are in practice today is that they often require the use of instructions being spelled out in complete detail. Since, this is not always practical, engineers from Cornell University have come up with a new robot named 'Tell Me Dave' that is able to understand spoken command instructions even if they are not much detailed. For instance, if you say, "Make me a cup of coffee", the robot will is capable of performing the right actions depending upon its surroundings.

    Developed by Dipendra Misra, doctoral student, department of computer science, Jaeyong Sung and Prof. Ashutosh Saxena, Director, Robot Learning Lab, the robot is able to determine if it should fill a new cup with milk and which coffee to use from the available options. It can also decide if it should use the stove or the microwave, what temperature to boil water at and the amount of sugar to add. A demo of their robot working on VEIL-200 dataset can be found #-Link-Snipped-#.

    Tell-Me-Dave-Robot

    The team has developed an algorithm that lets the user input natural language commands and the environment in which to execute them and in return the robot outputs a sequence of instructions which can be executed by the robot using a latent-CRF model that is trained by the data given by users playing an online robotic simulator. Their model is trained from data given by people playing a virtual #-Link-Snipped-#. In the following video you can see a person controlling their virtual robot in first person perspective to complete the task of "make ramen" -


    What are your thoughts on the new robot 'Tell Me Dave'? Share your thoughts with us in comments.

    Source: #-Link-Snipped-#
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