Professor Shlomo Zilberstein has embarked on a National Science Foundation-funded project to explore the planning and challenges involved in automated planning for semi-autonomous systems. On this four-year NSF grant, he is working with Professor Donald Fisher from UMass Amherst Mechanical & Industrial Engineering and Claudia Goldman from General Motors R&D.
"Autonomous systems offer transformational impacts on society as they help reduce human labor, decrease risks and costs, and improve productivity and efficiency. They have been deployed in a wide range of domains from household products to space exploration vehicles," said Zilberstein. "In many areas, however, there are still considerable barriers to the deployment of fully autonomous systems. These barriers range from technological to ethical and legal issues. Examples include driving a car, robot deployment in search and rescue operations, automated farming, and robotic surgery. When full autonomy is not possible, it is desirable to automate parts of the process. But classical AI planning techniques are inadequate for these settings."
Zilberstein's project offers a comprehensive study of planning for semi-autonomous systems--systems that are capable of autonomous operation under some conditions, but may require manual control in order to complete the task at hand. "Planning for semi-autonomous systems is challenging because it must account for the different skills of the human operator and the automated system, the communication between them required to facilitate smooth transfer of control, the uncertainty about human responsiveness, engagement level and readiness to take over control, and the possibility of human error in interpreting or following the plan," noted Zilberstein. The project addresses both the computational challenges and the challenges that arise when humans are involved, with semi-autonomous driving as the primary focus. The team will be using several testbeds, including two realistic driving simulators to evaluate their research.