The researchers joined forces to disentangle how humans learn to coordinate input from their senses -- e.g. vision, touch -- with movements, like reaching for a glass or moving through a crowded room. They will then map out how machines, such as robots and computers, learn similar tasks, in order to model devices that can assist humans.
The team, which combines expertise in engineering, computer science, neuroscience, motor control and biomechanics, envisions a multifunctional array of sensors on the body and has already developed prototypes for some of the devices. The full complement of wearable sensors would help a sightless person navigate by conveying information about his or her surroundings.
Professor Zhu works on navigation and obstacle detection by robots. For the project, he will focus on machine sensing and computer learning to understand the human-computer interaction.
He will also refine displays that would feed information from electronic sensors to the human wearer of the device. His lab is already testing a sensor that can detect proximity to an object and convey its distance with vibration on the hand or other body part. As one gets closer to a table, for example, it gradually increases the intensity of the stimulation.
Professor Ro, a neuroscientist, will provide a window into what is going in the brain as sighted and visually impaired individuals navigate a room or virtual environment with and without devices to assist them. Using Professor Zhu's distance sensor, he is now testing how sensitive people are in discriminating vibrations to the hand that tell them how far it is from an object. He will determine whether they can make accurate judgments and whether they might be using the visual parts of the brain.
Professor Tian works on higher-level
|Contact: Jessa Netting|
City College of New York