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A Wheelchair With Ears and Brain

Whilst the days that wheelchairs are no longer necessary are long wished for, they are not in sight yet. So, any advance on wheelchair technology that makes life easier for someone confined to one, is greatly welcomed.

At MIT, researchers are working on an artificially intelligent electric wheelchair, designed to aid the least mobile individuals with navigation.

Using a variety of SLAM (simultaneous Location and Mapping) pathfinding technology, the whelchair over time learns the constraints and boundaries of the world it is able to safely navigate or access. Controlled by voice commands, it is intelligent enough to under stand a command like "Take me to the cafeteria", and pull up its own internal maps of current position versus desired position, then drive the person there, deciding on the individual twists, turns, and collision avoidance for itself..

"It's a system that can learn and adapt to the user," says Nicholas Roy, assistant professor of aeronautics and astronautics and co-developer of the wheelchair. "People have different preferences and different ways of referring" to places and objects, he says, and the aim is to have each wheelchair personalised for its user and the user's environment.

Unlike other attempts to program wheelchairs or other mobile devices, which rely on an intensive process of manually capturing a detailed map of a building, the MIT system can learn about its environment in much the same way as a person would.

By being taken around once on a guided tour, the wheelchair tunes in on a person's voice and learns to associate geospatial locations with words uttered. 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." That is all that's needed. From that, the wheelchair internally memorises those locations.

Outdoors in the open, such systems can rely on GPS receivers to figure out where they are, but inside buildings that method usually doesn't work, so other approaches are needed. Roy and Teller have been exploring the use of WiFi signals, as well as wide-field cameras and laser range finders, coupled to computer systems that can construct and localise within an internal map of the environment as they move around.

Video courtesy Nicholas Roy

For now, the wheelchair prototype relies on a WiFi system to make its maps and then navigate through them, which requires setting up a network of WiFi nodes around the facility in advance. After months of preliminary tests on campus, they have begun trials in a real nursing home environment with real patients, at the Boston Home in Dorchester, a facility where all of the nearly 100 patients have partial or substantial loss of muscle control and use wheelchairs.

Also collaborating on the project are Bryan Reimer, a research scientist at MIT's AgeLab, and Seth Teller, 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).

Teller says the RVSN group is developing a variety of machines, of various sizes, that can have situational awareness, that is, that can "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 range in scale from a location-aware mobile phone all the way up to an industrial forklift that can transport large loads from place to place outdoors, autonomously.

"I'm interested in having robots build and maintain a high-fidelity model of the world," says Teller, whose central research focus is developing machines that have situational awareness.


A Wheelchair With Ears and Brain

Robust Robotics Group, MIT

Robost Robotics Current Research: Human-Robot Interaction for Assistive Robots

Boston Home

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