Andrew Sabelhaus Receives NSF CAREER Award, Advancing the Safety of Soft Robots for Human and Environmental Interactions

By Hariri Institute Staff

Andrew Sabelhaus, an ENG assistant professor of mechanical engineering and systems engineering (affiliate) has received a prestigious National Science Foundation (NSF) Faculty Early Career Development Program (CAREER) award.

As director of the Soft Robotics Control Lab at Boston University, Sabelhaus leads research that advances the safety of soft robots for human and environmental interactions. His work combines computational intelligence with embodied intelligence, delivering a control-oriented approach to the locomotion of soft and flexible robots and their interaction with humans. His work seeks to make soft robots practical and applicable, allowing a robot to safely complete tasks in unstructured environments.

With the NSF CAREER award, Sabelhaus aims to develop autonomous artificial intelligence (AI) systems that bring a soft robot into close contact with humans during verifiably-safe motion. The project reframes the control of soft robots as a specification satisfaction problem, rather than motion tracking, no matter how safety is defined.

“The hope that soft robots are safer around humans neglects how multi-faceted the robot’s tasks may be, and how safety depends on much more than reducing accidental forces,” says Sabelhaus. “For example, a soft robotic arm assisting in a medical procedure must meet constraints on both too much pressure as well as not enough pressure on a patient’s body, as well as timing and in sequencing of its actions.”

The project’s novelty is the first application of safe-by-construction control to soft robots, as well as the focus on unique challenges therein such as controllable stiffening of the robot, lack of highly accurate mathematical models, and changes to the robot over time. This project’s impacts are in the potential to make common medical procedures low-cost and widely accessible, while reducing biases arising from subjective clinician decisions about patient comfort and pain tolerance.

Read the project abstract here.