Journal
IEEE ACCESS
Volume 9, Issue -, Pages 68289-68301Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/ACCESS.2021.3077521
Keywords
Planning; Satellites; Machine learning; Data mining; Transforms; Process control; Computer architecture; Automated planning; domain rule learning; machine learning; PDDL
Ask authors/readers for more resources
This paper presents an automated planning process with restrictions to prevent invalid states, ensuring higher quality plans and better performance during execution. The method involves implementing a validator to match plan generation with imposed domain restrictions, contributing to reduced computational resources.
The increase of automated systems in space missions raises concerns about safety and reliability in operations carried out by satellites due to performance degradation. There have been several studies about the automatic planning process, but many approaches are generated with invalid states. The invalid state can be understood as a prohibited, degraded or risky scenario for the domain. This paper proposes an automated planning process with restrictions that enables automatic planners to not generate plans with invalid states. We implement a validator method for the planner software which proves that plan generation matches the restrictions imposed on the domain. In the experiments, we test an automatic planning process that is specific to the aerospace area, where a knowledge base with invalid states is available in the context of the operation of a satellite. Our proposal to carry out the verification of invalid states in automatic planning, can contribute to plans being generated with higher quality, ensuring that the goal of a plan is only achieved through valid intermediate states. It is also expected that the generated plans will be executed with better performance and will require less computational resources, since the search space is reduced.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available