Autonomous Vehicles and Robotic Systems with Human-in-the-Loop Guidance

Professor: Ross Greer

Description: Hazardous events create a need for human intervention in autonomous planning algorithms. This project will involve the creation of datasets to facilitate these interventions, pairing human communication with autonomous responses to facilitate feature extraction and pattern learning for complex motion planning. After collecting data, algorithms will be developed for aligning generated motion to the nonverbal or verbal guidance. Students will gain experience in intelligent vehicle data curation and collection, computer vision, and machine learning.

Preferred Qualifications: Python programming