Thursday, January 25, 2018
2:30 p.m. – 3:30 p.m. Central

Room 102
Mechanical Engineering Building
University of Minnesota
111 Church Street SE
Minneapolis, MN

Watch the live webcast

About the Seminar

This presentation will describe efforts to produce an autonomous navigation framework in which the various components of the architecture work together to minimize the size, computation, and power required to achieve a robust sensing and navigation package. This includes a lightweight lidar odometry framework that extracts and relies on a small number of descriptive features to localize a ground vehicle, a real-time scan-by-scan terrain traversability mapping algorithm, and a hierarchical multiobjective motion-planning framework that is capable of safe and efficient decision making over these maps. These concepts will be demonstrated using the presenter's Clearpath Jackal electric unmanned ground vehicle (UGV).

The presentation will also discuss the potential for machine learning techniques to outperform the costly optimization-based approaches that are repeatedly invoked in many UGV perception and decision-making processes. Although expensive to train, approaches such as deep learning with convolutional neural nets offer the promise of fast and scalable query time, and preliminary results will be presented in pursuit of this goal.

Applications to problems such as autonomously clearing snow on a campus driveway (in a GPS-unfriendly environment) and the detection and avoidance of pedestrians will be also be discussed.

About the Speaker

Brendan Englot

Brendan Englot is an assistant professor of mechanical engineering at Stevens Institute of Technology, where he directs the Robust Field Autonomy Lab. The lab focuses on robust autonomous navigation solutions for robots operating in harsh and unstructured environments. He previously worked at United Technologies Research Center, where he was a research scientist and principal investigator in the Autonomous and Intelligent Robotics Laboratory and a technical contributor to the Sikorsky Autonomous Research Aircraft.

Webcast

Watch the live webcast

The webcast will be broadcast using YouTube Live. To test your computer or mobile device's compatibility with YouTube Live, please visit the YouTube Live website, where you will have access to a number of events streaming in real time. If you are able to view any of these events, your device will be compatible with the seminar presentation. Please access the YouTube Help Center if you need assistance.

More Information

There is no cost to attend, and registration is not required. For more information, please contact Chelsea Arbury at arbur001@umn.edu or 612-626-2862.

Parking and Transit

Parking is available at the Washington Avenue Ramp, the Church Street Garage, or the University Avenue Ramp. For transit information, please visit the Metro Transit website or call 612-373-3333.