Verification of Planning-based Autonomous Systems

Drilling wells is a complex and potentially dangerous process in which equipment failures, unexpected environmental effects due to the poorly understood subsurface, and human errors can lead to potentially catastrophic outcomes. In an effort to reduce the likelihood of these as well as the cost of drilling, Schlumberger is developing systems that can operate autonomously or semi-autonomously as part of human/machine teams in complex, dangerous and uncertain environments. Such systems must be able to respond appropriately to unexpected events, and a significant challenge in deploying them is in verifying that the system is safe, and that it will detect and respond to critical events appropriately. This is particularly challenging in drilling as the systems tend to be sensor poor, and even leaving the system in a safe state in response to an event often involves a non-trivial sequence of activities.

In this project we aim to provide automated support to verify planning-based autonomous systems. In particular, we will focus on investigating techniques to improve the efficiency and effectiveness of planning domain model verification, including formal methods and test-based techniques.

People

PhD student: Anas Shrinah

Primary supervisor: Prof. Kerstin Eder

Industrial supervisor: Prof. Derek Long


Affiliated to Schlumberger Cambridge Research Centre:

Dr. Inês Cecílio (R&D Programme Manager & Senior Scientist)
Dr. Peter Gregory (Senior Research Scientist)