Reliable Plan Selection with Quantified Risk-Sensitivity

Tobias John, Mahya Mohammadi Kashani, Jeremy P Coffelt, Einar Broch Johnsen, Andrzej Wasowski

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


Robots in many domains need to plan and make decisions under uncertainty; for example, autonomous underwater vehicles (AUVs) gathering data in environments inaccessible to humans, need to perform automated task planning. Planning problems are typically solved by risk-neutral optimization maximizing a single objective, such as limited time or energy consumption. A typical probabilistic planner synthesizes a plan to reach the desired goals with a maximum expected reward, given the possible initial states and actions of the world. In this work, we additionally consider risk metrics for selecting solutions to such planning problems. Consider a marine robotics mission scenario where the task is to survey pipeline segments safely based on various risk measurements.
Original languageEnglish
Title of host publicationNWPT 2023 - 34th Nordic Workshop on Programming Theory
Publication date2023
Publication statusPublished - 2023
EventNWPT 2023 - 34th Nordic Workshop on Programming Theory - Mälardalen University, Västerås, Sweden
Duration: 22 Nov 202323 Nov 2023


WorkshopNWPT 2023 - 34th Nordic Workshop on Programming Theory
LocationMälardalen University
City Västerås


  • Reliability engineering
  • Planning
  • marine robotics
  • risk assessment


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