A causal-based approach to explain, predict and prevent failures in robotic tasks

Author:

Diehl MaximilianORCID,Ramirez-Amaro Karinne

Publisher

Elsevier BV

Subject

Computer Science Applications,General Mathematics,Software,Control and Systems Engineering

Reference30 articles.

1. Towards robust task execution for domestic service robots;Kuestenmacher;Proceedings of the International Conference on Automated Planning and Scheduling,2014

2. On fault detection and diagnosis in robotic systems;Khalastchi;ACM Comput. Surv.,2018

3. The Book of Why: The New Science of Cause and Effect;Pearl,2018

4. Explanation in artificial intelligence: Insights from the social sciences;Miller;Artificial Intelligence,2019

5. The relevance of causation in robotics: A review, categorization, and analysis;Hellström;Paladyn, J. Behav. Robot.,2021

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2. Performance Guarantee for Autonomous Robotic Missions using Resource Management: The PANORAMA Approach;Journal of Intelligent & Robotic Systems;2024-03-22

3. Reactive or Proactive? How Robots Should Explain Failures;Proceedings of the 2024 ACM/IEEE International Conference on Human-Robot Interaction;2024-03-11

4. Generating and Transferring Priors for Causal Bayesian Network Parameter Estimation in Robotic Tasks;IEEE Robotics and Automation Letters;2024-02

5. CAR-DESPOT: Causally-Informed Online POMDP Planning for Robots in Confounded Environments;2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS);2023-10-01

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