9 citations · 15 across the 17 of their papers we have counts for
7 papers · 1 filter
Aircraft Collision Avoidance Systems: Technological Challenges and Solutions on the Path to Regulatory Acceptance
Sydney M. Katz, Robert J. Moss, Dylan M. Asmar +3
Aircraft collision avoidance systems is critical to modern aviation. These systems are designed to predict potential collisions between aircraft and recommend appropriate avoidance…
Failure Probability Estimation for Black-Box Autonomous Systems using State-Dependent Importance Sampling Proposals
Harrison Delecki, Sydney M. Katz, Mykel J. Kochenderfer
Estimating the probability of failure is a critical step in developing safety-critical autonomous systems. Direct estimation methods such as Monte Carlo sampling are often impracti…
Probabilistic Parameter Estimators and Calibration Metrics for Pose Estimation from Image Features
Romeo Valentin, Sydney M. Katz, Joonghyun Lee +3
This paper addresses the challenge of probabilistic parameter estimation given measurement uncertainty in real-time. We provide a general formulation and apply this to pose estimat…
Efficient Determination of Safety Requirements for Perception Systems
Sydney M. Katz, Anthony L. Corso, Esen Yel +1
Perception systems operate as a subcomponent of the general autonomy stack, and perception system designers often need to optimize performance characteristics while maintaining saf…
Risk-Driven Design of Perception Systems
Anthony L. Corso, Sydney M. Katz, Craig Innes +3
Modern autonomous systems rely on perception modules to process complex sensor measurements into state estimates. These estimates are then passed to a controller, which uses them t…
Collision Risk and Operational Impact of Speed Change Advisories as Aircraft Collision Avoidance Maneuvers
Sydney M. Katz, Luis E. Alvarez, Michael Owen +4
Aircraft collision avoidance systems have long been a key factor in keeping our airspace safe. Over the past decade, the FAA has supported the development of a new family of collis…
Preference-based Learning of Reward Function Features
Sydney M. Katz, Amir Maleki, Erdem Bıyık +1
Preference-based learning of reward functions, where the reward function is learned using comparison data, has been well studied for complex robotic tasks such as autonomous drivin…