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A survey on embodied robot teleoperation
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Ziqiang NI, Shaoxuan XIE, Xuecheng LIU, Xiang YANG, You LIU, Guocai YAO*
Science & Technology Review | 2026, 44(13) : 28 - 39
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Science & Technology Review | 2026, 44(13): 28-39
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A survey on embodied robot teleoperation
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Ziqiang NI, Shaoxuan XIE, Xuecheng LIU, Xiang YANG, You LIU, Guocai YAO*
Affiliations
  • Beijing Academy of Artificial Intelligence, Beijing 100089, China
Published: 2026-07-13 doi: 10.3981/j.issn.1000-7857.2025.09.00103
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Embodied robot teleoperation will remain indispensable before robots can achieve fully human−level autonomy. This paper first categorizes human–machine interaction modalities for teleoperation, including exoskeletons, virtual/mixed reality, motion capture/inertial sensing, and vision−based interfaces. It then analyzes the evolution of teleoperation control paradigms, covering direct control, shared control, imitation−learning−based approaches, and the recent introduction of generative strategies, highlighting their underlying principles and application domains. Next, representative system architectures and technical implementations are introduced, encompassing perception and mapping, control algorithms, and communication modules, while discussing the role of multimodal feedback—such as vision, force, and touch—in enhancing immersion. Furthermore, performance evaluation methods and the latest benchmarks are reviewed, emphasizing the significance of open−source software/hardware platforms and data resources in advancing the field. Finally, the paper summarizes key challenges and future directions, including improving the level of intelligence, reducing costs and barriers to adoption, and establishing standardized frameworks.

embodied robots  /  teleoperation  /  human–machine interaction  /  control paradigms
Ziqiang NI, Shaoxuan XIE, Xuecheng LIU, Xiang YANG, You LIU, Guocai YAO. A survey on embodied robot teleoperation[J]. Science & Technology Review, 2026 , 44 (13) : 28 -39 . DOI: 10.3981/j.issn.1000-7857.2025.09.00103
Year 2026 volume 44 Issue 13
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doi: 10.3981/j.issn.1000-7857.2025.09.00103
  • Receive Date:2025-09-23
  • Online Date:2026-07-27
  • Published:2026-07-13
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  • Received:2025-09-23
  • Revised:2025-12-31
Affiliations
    Beijing Academy of Artificial Intelligence, Beijing 100089, China
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表12种不同金属材料的力学参数

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Number of
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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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