Dynamic path planning of autonomous bulldozers using activity-value-optimised bio-inspired neural networks and adaptive cell decomposition-Reference-Cited by-同舟云学术

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Dynamic path planning of autonomous bulldozers using activity-value-optimised bio-inspired neural networks and adaptive cell decomposition

Published:2024-10 Issue: Volume:164 Page:111944
ISSN:1568-4946
Container-title:Applied Soft Computing
language:en
Short-container-title:Applied Soft Computing

Author:

Meng Xiangyun,Gao Haojun,Wang Jiajun^ORCID,Wang Xiaoling,Yu Hongling,Zhang Jun

Publisher

Elsevier BV

Reference44 articles.

1. Multiagent robotic systems and exploration algorithms: Applications for data collection in construction sites;Prieto;J. FIELD Robot.,2024

2. Attaining digital transformation in construction: An appraisal of the awareness and usage of automation techniques;Oke;J. Build. Eng.,2023

3. Research Status Quo and Trends of Construction Robotics: A Bibliometric Analysis;Wu;J. Comput. Civ. Eng.,2024

4. An imitation from observation approach for dozing distance learning in autonomous bulldozer operation;You;Adv. Eng. Inform.,2022

5. Construction path tracking and pose estimation of unmanned bulldozer;Peng;Autom. Constr.,2023

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