UMass Lowell Assistant Professor Reza Ahmadzadeh envisions a future world where robots help people live more comfortably and safely—and he’s working to develop the methods to make such an environment possible.
The National Science Foundation recognized the potential of Ahmadzadeh’s perspective and awarded him a faculty early-career development CAREER grant. The nearly $500,000 pays for Ahmadzadeh’s project on robot learning of complex tasks over the next five years.
“I hope to get to a place where we use robots in our everyday lives,” said Ahmadzadeh.
Since his time as a doctoral student in robotics, cognition and interaction technologies at the University of Genoa, Ahmadzadeh has focused his research on robots learning from human demonstration. He explained, this can be accomplished through kinesthetic teaching, where a person holds the robot and moves it around, or through the robot “watching” the person via feeds from a virtual reality headset, joystick or camera.
The information gathered from the human demonstration is then sent to algorithms programmed within the robot. Existing algorithms work well for replication of simple tasks, such as picking up an object, “but human life is not just made of simple tasks,” said Ahmadzadeh.
For his NSF CAREER project, Ahmadzadeh will develop new algorithms for robots to learn complex tasks.
The prospective breakthroughs from this project could help automate difficult and dangerous duties in the workplace, freeing up employees’ time to pursue more creative or higher-value projects. It could also help older adults remain in their homes longer by assisting them with daily chores.
“The results of Ahmadzadeh’s funded research will have a great impact on how people work with robot systems in the future,” said UMass Lowell robotics Professor Holly Yanco. She is the director of the UMass Lowell New England Robotics Validation and Experimentation, or NERVE, Center which just celebrated a decade of innovation.
“If a robot is sent into a human’s home now, they will not be useful with complex tasks,” said Ahmadzadeh. “The robot could learn to hand a person a light bulb, but it wouldn’t be able to change it.”
Ahmadzadeh plans to review studies in human movement to see if algorithms used for primitive skills in robots can be improved. He then will seek new approaches that allow robots to string together a library of reusable skills to accomplish complex tasks.
He will also build algorithms that let a robot discover the skills needed to finish a job. “If a human shows a robot how to make coffee, the robot may know how to pick up a mug and place it, but not how to press the button on the machine,” he said. “The robot would be able to grab that skill and put it in its library to be used again later.”
With this funding, Ahmadzadeh will create methods to refine the robot’s skills so it can complete a task no matter the environment.
“A human would give another demonstration, and the robot would realize that this is the same skill but applied to a new situation, so it would refine what it already knows,” he says.
Undergraduate and graduate students will be assisting Ahmadzadeh with his research, which will lead to a revamping of his Robot Learning course. Students will also be exposed to robot learning during one-day workshops that Ahmadzadeh plans to hold throughout the duration of the project. The workshops will run as part of SoarCS, a summer program for incoming first-year computer science students.