The Personal Assistance for Object Delivery (PAOD) is developed to automate the delivery of items, thereby increasing the convenience and efficiency of daily chores. The goal is to develop a robot as a personal assistant, navigate it to the destination through the prescribed path and program it to deliver the specific object to the intended recipient. The master controlling the robot and the recipients are identified through face recognition algorithm. Voice commands are used to interact with the robot. It is versatile enough to be used in homes, workplaces, hospitals, and other settings since it can handle a wide range of objects, regardless of size or shape. The PAOD ensures that the object is delivered to the right person and in-time. Face recognition is one of the PAOD's most notable capabilities since it enables the robot to recognize the intended receiver for delivery. This lowers the possibility of mistakes by guaranteeing that the correct individual receives the object. Additionally, users may communicate with the robot hands-free because to the PAOD's support for voice commands. As a result, controlling the robot without manual input and giving instructions is simple. The PAOD also has autonomous navigation skills, allowing it to navigate through a variety of situations, overcoming obstacles and determining the best course of action. By giving users real-time status updates, the robot keeps the master updated on the status of the delivery. PAOD is a flexible, hands-free object delivery robot that is intended to increase productivity, decrease effort and improve efficiency in daily chores. The accuracy of 97.5 % is achieved in the master and recipient identification. Destination would be reached within error of $\pm 10 ~\text{cm}$.


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    Title :

    Personal Assistance for Object Delivery


    Contributors:
    H, Harshini A (author) / S, Jyotsna K (author) / V, Sneha (author) / G, Ankitha (author) / Rao, A N Mukunda (author)


    Publication date :

    2025-03-21


    Size :

    3247258 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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