App. Res. of Comp. Accepted Paper
Vol. 43, 2026 No. 10

Robot multi-task imitation learning algorithm based on improved visual features and textual semantics

Wen Wentaoa,b
Chen Kaia,b
Du Yuhenga,b
Zheng Huaqianga,b
Liu Weiyea,b
Yuan Yea,b
Liu Naa,b
a. Institute of Machine Intelligence, b. School of Health Science & Engineering, University of Shanghai for Science & Technology, Shanghai 200093, China
DOI: 10.19734/j.issn.1001-3695.2026.03.0040

Abstract

To address the issues of insufficient generalization and multi-modal fusion difficulties in robot imitation learning within unstructured scenarios, this paper proposes an improved multi-task imitation learning algorithm fusing visual features and textual semantics. The proposed method utilizes pre-trained models to extract multi-modal features, introduces a cross-attention mechanism to achieve deep alignment between vision and semantics, and incorporates an action chunking module to enhance control policy precision. Simulation experiments demonstrate that the proposed method achieves a 98% success rate in both object transmitting and table cleaning tasks, outperforming the ACT method by 6 and 10 percentage points, respectively. Under identical experimental settings, the model's peak GPU memory usage is 2100 MB, significantly lower than the 8200 MB of RT-1 and 3400 MB of ACT. The results indicate that this method effectively improves the robot’s multi-task switching capability and action generation stability in unstructured scenarios.

Foundation Support

国家重点研发计划资助项目(2023YFC3605800)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2026.03.0040
Publish at: Application Research of Computers Accepted Paper, Vol. 43, 2026 No. 10

Publish History

[2026-07-30] Accepted Paper

Cite This Article

温文涛, 陈凯, 杜禹恒, 等. 基于改进视觉特征与文本语义的机器人多任务模仿学习算法 [J]. 计算机应用研究, 2026, 43 (10). (2026-07-30). https://doi.org/10.19734/j.issn.1001-3695.2026.03.0040. (Wen Wentao, Chen Kai, Du Yuheng, et al. Robot multi-task imitation learning algorithm based on improved visual features and textual semantics [J]. Application Research of Computers, 2026, 43 (10). (2026-07-30). https://doi.org/10.19734/j.issn.1001-3695.2026.03.0040. )

About the Journal

  • Application Research of Computers Monthly Journal
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    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

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