February 13, 2019
Abstract: This is a two-part talk verification of driverless vehicles and generating safe missions aerial vehicles.
1. A Driver’s License Test for Driverless Vehicles - Autonomous vehicles (AVs) have driven millions of miles on public roads, but even the simplest scenarios, such as a lane change maneuver, have not been certified for safety. As there is no systematic method to bound and minimize the risk of decisions made by the vehicle’s decision controller, the insurance liability of autonomous vehicles currently is entirely on the manufacturer. I will describe APEX, a tool for autonomous vehicle plan verification and execution across a variety of driving scenarios. We will see the use of synthetic environments such as computer gaming and real DoT traffic feeds to train and evaluate machine learning and decision control algorithms in future AVs.
2. Fly-by-Logic: Autonomous Air Traffic Control for Safe Drone Missions - Safe planning and control of multi-drone fleets performing complex missions has been a challenging problem. Methods that offer guarantees on safety and mission satisfaction generally do not scale well. On the other hand, more computationally tractable approaches do not offer any safety guarantees. In this talk, I will present a method that overcomes these limitations for a wide variety of multi-drone missions that consist of a combination of the following objectives:
1) spatial objectives, e.g. geofenced no fly zones, or delivery zones,
2) temporal objectives, e.g. a time window to monitor wireless signal strengths in an area,
3) reactive objectives, e.g. in case of a drone failure, another drone picks up its mission.
We show the performance, scalability and real-time applicability of our method through simulations and experiments on actual quadrotor drones.
Bio: Prof. Mangharam is a professor in the Dept. of Electrical & Systems Engineering and Dept. of Computer & Information Science at the University of Pennsylvania. His interests are in cyber-physical systems at the intersection of formal methods, machine learning and controls. He is the Penn Director for the Department of Transportation's $14MM Mobility21 National University Transportation Center [2017-2022]. Rahul received the 2016 US Presidential Early Career Award (PECASE) from President Obama for his work on Cyber-Physical Systems. He also received the 2016 Department of Energy’s CleanTech Prize (Regional), the 2014 IEEE Benjamin Franklin Key Award, 2013 NSF CAREER Award, 2012 Intel Early Faculty Career Award and was selected by the National Academy of Engineering for the 2012 US Frontiers of Engineering. He has won several ACM and IEEE best paper awards. He received his Ph.D. in Electrical & Computer Engineering from Carnegie Mellon University where he also received his MS and BS in 2007, 2002 and 2000 respectively.