- Perception, Planning and Control Algorithms for Off-road Vehicles: To develop and deploy autonomous off-road vehicles for Department of Defense applications.
- GPS-denied, Estimation and Navigation: To develop robust algorithms for estimating the state (position, attitude and velocity) of unmanned aerial and ground vehicles (UxVs) in GPS-denied environments using a combination of vision, LIDAR and inertial sensors.
- Perception and Planning Algorithms for Shuttles: To develop and deploy autonomous shuttles on campus with the goal of developing autonomous vehicles for paratransit applications
- Perception and Planning for Autonomous Trucks: Develop control, perception and planning algorithms for autonomous trucks.
- Collaborative Localization and Planning: This project deals with developing algorithms for collaborative localization of UAVs as a group in GPS-denied environments, as well as for collaborative “localization-aware” planning under uncertainty.
- Obstacle Avoidance, Mapping and Navigation: The focus is on developing algorithms for obstacle avoidance based on computer vision for ground, fixed-wing and rotary aerial vehicles
- Autonomous Landing on Moving Targets: This work deals with the design and implementation of a real-time, vision-based landing algorithm for an autonomous helicopter. The landing algorithm is integrated with algorithms for visual acquisition of the target (a helipad), and navigation to the target, from an arbitrary initial position and orientation. We plan to use vision for precise-target detection and recognition, and a combination of vision and GPS for navigation
Autonomous Shuttles
We focus on developing and deploying low-speed shuttles on campus, urban environments/downtowns and in other areas. Along with this, we educate the public about the current state-of-the-art in autonomous vehicles, as well as the drawbacks. Our goal is to focus on human-vehicle interaction, pedestrian behaviors/interaction, vehicle certification, and large-scale vehicle deployments and interactions for improved safety and trust.