IEEE Transmitter Expert Sharing – Prof. Ming LIU

Three of the robotics researchers were selected by the IEEE publicity department globally. This year, Prof. Ming LIU from HKUST-Robotics Institute was invited by IEEE Transmitter to represent the Greater China Region to share his knowledge on “Robotic Learning”. His robot is a mobile, unmanned ground vehicle with visual sensors that allow it to perform autonomous driving tasks.

Prof LIU’s speciality is mobile robotic navigation, as well as how robots perceive their environment, how they interact with humans and how they learn. He explains in the video that there are two ways that robots can learn, the traditional way or through deep data based learning. The traditional way uses the Simultaneous Localization Area Mapping (SLAM) program. This allows the robots to move in unknown environments and while it is moving, the robot is able to create a map of the area. The robot will learn in real time. Deep data based learning can take longer, as the robot starts with basic knowledge and collects experiences as it operates, building its own knowledge base.

Link to IEEE Page and Video

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