'Robot Sensor Fusion for Multimodel Tracking and Recognition of Humans'
The lecture covered ways in which a robot can detect human presence. Throguh face recognition and leg and torso detection, the three combined produce a fairly reliable source through which to gather data and predict if a human being is stood in front of it.
The camera is combined with a laser sensor, the camera for face and torso detection and laser for leg detection. Either legs apart, at an angel or close together can be detected and identified by the program. Through the use of the laser sensor the robot can also navigate through a complex environment by detecting other obstacles, which allows it to track the people it has detected.
Nicola Bellotto
'Closing the HRI loop: Two way emotion interaction in human robot interaction'
Human Robot Interaction is the core subject of this lecture. Though input is focussed on in great depth, feedback is never overly user friendly. For example, a number of beeps could represent the feedback, which is never novice-friendly.
Robots with facial expressions have been used in an investigation into new feedback methods and has been successful. ERWIN, Emotion Robot With Intelligent Networks, is such a robot. when a participant interacts with the robot the in built camera uses face detection to send a command to which emotion to show.
The results are promising and with research into this area of robotics, much more is likley to be developed.
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