Robot Wheelchair Directed by Voice Command

A new type of autonomous wheelchair is capable of learning the topography of any given building, and subsequently transport its occupant to a given location in response to a verbal command.

Researchers at the Massachusetts Institute of Technology (MIT, Cambridge, MA, USA) are developing a variety of machines, of various sizes, that can have situational awareness, learning and mapping their environment. One of these machines is a wheelchair prototype that relies on a wireless WiFi system and its various nodes to generate positional maps, and then navigate itself through them. Thus, the wheelchair user would be able to avoid the need for controlling every twist and turn of the route and could simply sit back and relax as the chair moves from one place to another, based on a map stored in its memory. As research progresses, the developers intend to add a collision-avoidance system using detectors to prevent the chair from bumping into other wheelchairs, walls, or other obstacles. In addition, they hope to add mechanical arms to the chairs, to aid the patients further by picking up and manipulating objects--from flipping a light switch to picking up a cup and bringing it to the person's lips.

The wheelchair system can learn about its environment in much the same way as a person would: By being taken around once on a guided tour, with important places identified along the way. For example, as the wheelchair is pushed around a nursing home for the first time, the patient or a caregiver would say: "this is my room" or "here we are in the foyer" or "nurse's station." After months of preliminary tests on the MIT campus, the researchers have begun trials in a real nursing home environment with real patients, in a facility where all of the nearly 100 patients have partial or substantial loss of muscle control and use wheelchairs.

"I'm interested in having robots build and maintain a high-fidelity model of the world,” said one of the developers, Seth Teller, Ph.D., a professor of computer science and engineering and head of the Robotics, Vision, and Sensor Networks (RVSN) group at MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL). "They learn these mental maps in order to help people do what they want to do, or do it for them.”

Besides the wheelchair, the devices being developed range in scale from a location-aware cellular phone all the way up to an industrial forklift that can transport large loads from place to place outdoors, autonomously.

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Massachusetts Institute of Technology