Evolving Behavior Trees for Self-Adaptive Source Searching in Indoor Environments
Created by W.Langdon from
gp-bibliography.bib Revision:1.8028
- @InProceedings{Ma:2023:ICUS,
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author = "Xinyu Ma and Hai Zhu and Xiaozhou Zhu and Wen Yao",
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booktitle = "2023 IEEE International Conference on Unmanned Systems
(ICUS)",
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title = "Evolving Behavior Trees for Self-Adaptive Source
Searching in Indoor Environments",
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year = "2023",
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pages = "1003--1008",
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abstract = "This paper presents a self-adaptive source searching
approach using evolved Behaviour Trees (BTs). Robots
often face challenges in making comprehensive decisions
during source searching due to difficulties in
integrating sensor information and adjusting policies
based on varying states and events. Behaviour Trees
offer a modular framework for combining perceptions
with corresponding actions, enabling robots to make
informed decisions across different source searching
stages. The proposed approach incorporates strategies
from reactive methods and Infotaxis into BT nodes, with
the source searching policies evolved through Genetic
Programming. To enhance evolution, we introduce a
substitution-based synthesis method for initial BTs and
a parallel execution approach for fitness evaluation.
Experimental results demonstrate that the proposed
method outperforms Infotaxis with a 21.8percent
increase in success rate and a 35.9percent decrease in
average steps, and outperforms the reactive strategies
with a 77.7percent increase in success rate and a
46.3percent decrease in average steps. While our method
may exhibit lower performance compared to standard
Infotaxis in certain wind conditions, it effectively
reduces computational complexity without significant
performance degradation.",
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keywords = "genetic algorithms, genetic programming, Degradation,
Solid modelling, Robot sensing systems, Data models,
Stability analysis, Behavioural sciences, source
searching, Behaviour Trees, Infotaxis",
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DOI = "doi:10.1109/ICUS58632.2023.10318502",
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ISSN = "2771-7372",
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month = oct,
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notes = "Also known as \cite{10318502}",
- }
Genetic Programming entries for
Xinyu Ma
Hai Zhu
Xiaozhou Zhu
Wen Yao
Citations