Our goal is to create a user-friendly and safe autonomous driving cleaning robot for large-scale cobblestone areas or parking lots. Primary target group of our product is the semi-professional part of the autonomous cleaning robot market. The ACC 3000 robot is designed with two motions and one 360-degree environment IR sensor and a recharge station with an inbuilt Wi-Fi device to monitor the robot. The robot can drive anywhere if no obstacles are detected. The ground is flat, the inclination does not exceed 5 degrees and the Wi-Fi connection is not lost. When switched on, the controller inside gets continuously updated on the health parameter, e.g., battery status and obstacle detection by the help of the sensors. The robot is controlled and can be monitored by an app on a smart phone. Simple commands, such as ON/OFF switch, route mapping and two different rotational speeds of the wire brushes are possible to set up. For example, setting up the system for higher rotational speeds of the wire brushes ensures to remove even persistent plant or moss infestation in between gaps of the ground surface. Our competitive advantage is that our cleaning robot is made of durable and cost-efficient materials and will save household costs as a long-term investment by removal of labour cost of expensive workers. There are no other autonomous cleaning robots at this price available that match our design and usability, which makes our product unique in the market. We will start production and sales in Germany with plans to later expand into the European, North American, and Asia-Pacific region. Our product pitch, design concept, and features are presented in an audio-visual format and is awarded the Science Communication ‘Gold Leaf Prize’ for an outstanding online video presentation in the category of ‘Audience Choice’ on January 18th, 2022.


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    Titel :

    ACC 3000: Autonomous Cobblestone Cleaning-robot



    Erscheinungsdatum :

    13.05.2022


    Medientyp :

    Sonstige


    Format :

    Elektronische Ressource


    Sprache :

    Englisch


    Schlagwörter :

    Klassifikation :

    DDC:    629 / 62




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