As a master's candidate at MIT, Yanco started thinking about wheelchairs after meeting David Miller, a visiting research scientist who organized the first robotic wheelchair exhibit at the 1995 International Joint Conference on Artificial Intelligence. That's where Yanco introduced an early version of Wheelesley. Although she intended to work on robotic vision for her PhD, she gravitated back to wheelchairs when her thesis advisor, robotics guru Rodney Brooks, observed that she seemed more excited when she talked about Wheelesley. After earning her PhD, she taught at Boston College for two semesters before UMass Lowell recruited her to start its robotics lab. Wheelesley, of course, went along for the ride.

Before Wheelesley, most robotic wheelchairs were usable only indoors, and many relied on known maps. But Yanco wanted to create a chair that could understand where a user wanted to go and avoid outdoor obstacles to get there. She's developing a new version of Wheelesley (known as Wheeley) that will be able to learn the most direct route to any location by updating an internal map, just as humans do. Two cameras serve as Wheeley's eyes, collecting the information it uses to build its map. (Positioned about four inches apart, the cameras work in stereo to give the robot depth perception.) Software designed by one of Yanco's collaborators lets it interpret the optical characters that appear in signs, including numbers, letters, and punctuation; the ability to interpret arrows and other symbols is in the works. Soon Wheeley will be able to recognize door handles and elevator buttons as well.

In addition to enhancing Wheeley's intelligent mapping, ­Yanco's group is working on improving robotic arm attachments that can recognize and grasp objects. Though such devices already exist, they are not only expensive--the Assistive Robotic Manipulator (ARM) made by the Dutch company Exact Dynamics costs $15,000 and up--but also hard to manage. Those who want to use the ARM must undergo several training sessions and study a thick manual detailing a complex series of joystick movements. Yanco envisions a robot that can figure out how to retrieve any object the user indicates.

At Lowell, Yanco and doctoral candidate Kate Tsui have developed an intuitive system for controlling the ARM. A user sitting in a wheelchair outfitted with the attachment and a touch screen will be able to touch an image of an object on the screen to tell the robotic arm to retrieve the object. Yanco has also added two color cameras, one on the ARM's shoulder and a smaller one between the two fingers of its gripper. Images from the cameras, displayed on a separate color touch screen, show what's in front of the attachment. In the lab, the ARM is mounted on a tripod about waist high in front of three wooden shelves containing nine objects, such as a coffee mug, a bottle of Advil, and several cups of different colors. When Tsui taps the image of a blue plastic cup on-screen, the 32-inch arm slowly unfurls, rotating at its shoulder and wrist, and extends so that its gripper hovers near the correct cup, which it identifies by color. Software developed by Yanco's colleagues at the University of Central Florida enables the ARM to grasp and retrieve the object.Yanco's group has started testing the touch screen and arm at the Crotched Mountain Rehabilitation Center in New Hampshire, where wheelchair users report that it is easy to use.

Yanco's group is also developing a low-cost arm attachment that can open doors. A prototype of the new arm's gripper, which can open, close, and turn in either direction, is powered by only one motor, to keep the arm within the $1,000-to-$2,000 range. The prototype opens a door when a user points a beam of light at it with a joystick-controlled laser. But ultimately, Yanco hopes to make it smart enough to reach for doorknobs automatically.