A Review and Prospect of Excavator Intelligence

Yi Li; Guangzhong Hu

doi:10.62051/ijmee.v8n4.04

Authors

Yi Li
Guangzhong Hu

DOI:

https://doi.org/10.62051/ijmee.v8n4.04

Keywords:

Excavator, Intelligent, Environmental Perception, Trajectory Planning, Remote Control, Digital Twin, Autonomous Operation

Abstract

Excavators are important equipment in many construction projects. In the process of intelligentisation, the technological advancements they have undergone are no longer covered solely by hydraulic technology, but are being explored from multiple perspectives towards the integration of mechanical, electrical, and hydraulic systems. In recent years, the industry has made certain progress in three-dimensional environmental perception and remote operation, and some key technologies have initially established a foundation for engineering applications. However, due to the poor robustness of perception systems and the difficulty of establishing accurate models under complex working conditions, a high level of autonomous operation capability cannot yet be achieved. These issues need to be addressed in the future for excavators to enter the era of intelligentisation

References

[1] Cao Youke. A brief study on the intelligent design of hydraulic excavators [J]. Global Market, 2016(35): 225, 227.

[2] Lv Qihui, Wang Lifu. Design and Research on Intelligent Control of Hydraulic Excavator Working Devices[J]. Modern Manufacturing Engineering, 2007(4): 107-109.

[3] Ding Pan, Pang Xiaoping, Chen Jin. Design of an Excavation Robot Visual Tracking System Based on Long Short-Term Memory Networks [J]. Mechanical Manufacturing and Automation, 2019(4): 145-148.

[4] Yu Huiting, Li Li. Intelligent Control System for Hydraulic Excavators[J]. Coal Mine Electromechanics, 2008(5): 31-34.

[5] Tan Chen, Song Weiqi. Research on Intelligent Design of Hydraulic Excavators[J]. Hydraulics and Pneumatics, 2016(9).

[6] Lu Liang, Wu Junkai, Sun Ning, et al. Intelligent Construction—Intelligentisation of Construction Machinery[J]. Hydraulics and Pneumatics, 2022(6): 1-9.

[7] Lian Chunping. Current Status and Development Trends of Intelligence in Large Mining Excavators [J]. Open-pit Mining Technology, 2023, 38(5): 70-73.

[8] Li Guihai. Design and Implementation of Visual Perception Algorithm for Intelligent Excavators [D]. Harbin: Harbin Institute of Technology, 2022: 12-49.

[9] Liu Wusong. Intelligent Mining Excavator Operational Environment Perception Based on 3D Point Cloud [D]. Dalian: Dalian University of Technology, 2022: 39-62.

[10] Xiao Ting, Wen Huaixing, Xia Tian. Intelligent Control System of Excavator Based on Binocular Recognition Technology[J]. Engineering Machinery, 2007(3).

[11] Liu Jian, Li Wenxin. Technical Route and Function Overview of Intelligent Trajectory Control for Excavators[J]. Construction Machinery, 2020(2).

[12] Zhang Xinrong, Kang Long, Tang Jiapeng, et al. Intelligent Excavator Trajectory Tracking Based on Variable Domain Fuzzy Multi-Parameter Self-Tuning PID Control[J]. China Journal of Highway and Transport, 2023, 36(2): 240-250.

[13] TIAN J, LIU Z J, ZHU W J, et al. Fuzzy rule-based section forming for mining robotic excavation error compensation[J]. IEEE Access, 2023, 11.

[14] LIN Y T, XIONG J Q, ZHU W L, et al. Research on the Prediction Method of Braking Rotation Angle for Remote-Controlled Excavator[J]. Sensors, 2023, 23(15).

[15] Liu Wenjie. Research on Vision-Based Intelligent Detection and Control Technology of Excavator Buckets[D]. Xuzhou: China University of Mining and Technology, 2023: 39-87.

[16] Yu Songsong, Liu Jian. Intelligent measurement system for effective load of hydraulic excavators [J]. Construction Machinery, 2023, 54(4): 54-57.

[17] Wei Jianlong. Research and Application of Intelligent Cluster Technology for WK Series Excavators[J]. Mechanical Engineering and Automation, 2024(3): 215-216.

[18] Zhang Zhe. Research on Intelligent Maintenance Application of Large Mining Shovel Excavators [J]. Southern Agricultural Machinery, 2019(8): 28.