Belief-based fault recovery for marine robotics

Jeremy Paul Coffelt, Mahya Mohammadi Kashani, Andrzej Wasowski, Peter Kampmann

Research output: Conference Article in Proceeding or Book/Report chapterArticle in proceedingsResearchpeer-review


We propose a framework expanding the capabilities of underwater robots to autonomously recover from anomalous situations. The framework is built around a knowledge model developed in three stages.
First, we create a deterministic knowledge base to describe the “health” of hardware, software, and environment components involved in a mission. Next, we describe the same components probabilistically, defining probabilities of failures, faults, and fixes. Finally, we combine the deterministic and probabilistic
knowledge into a minimal ROS package designed to detect failures, isolate the underlying faults, propose fixes for the faults, and determine which is the most likely to help. We motivate the solution with a camera fault scenario and demonstrate it with a thruster failure on a real AUV and a simulated ROV.
Original languageEnglish
Title of host publicationThe Eighth Joint Ontology Workshops (JOWO’22), August 15-19, 2022, Jönköping University, Sweden
Number of pages14
Publication date16 Aug 2022
Article numberpaper3-RobOntics
Publication statusPublished - 16 Aug 2022


  • ontology-based autonomy
  • marine robotics
  • fault detection and recovery
  • probabilistic logic programming


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