A review on manipulation skill acquisition through teleoperation‐based learning from demonstration

Si, Weiyong; Wang, Ning; Yang, Chenguang

doi:10.1049/ccs2.12005

Cited by 55 publications

(24 citation statements)

References 124 publications

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“…A detailed survey on teleoperation-based LfD can be found in refs. [101,102]. Li and Fritz [103] proposed an LfD method to teach the robotic arm with two fingers non-dexterous gripper to use the human tools.…”

Section: Imitation Learning (Il)mentioning

confidence: 99%

Review on human‐like robot manipulation using dexterous hands

Sampath

Wang

Wu³

et al. 2023

Cognitive Comp and Systems

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In recent years, human hand‐based robotic hands or dexterous hands have gained attention due to their enormous capabilities of handling soft materials compared to traditional grippers. Back in the earlier days, the development of a hand model close to that of a human was an impossible task but with the advancements made in technology, dexterous hands with three, four or five‐fingered robotic hands have been developed to mimic human hand nature. However, human‐like manipulation of dexterous hands to this date remains a challenge. Thus, this review focuses on (a) the history and motivation behind the development of dexterous hands, (b) a brief overview of the available multi‐fingered hands, and (c) learning‐based methods such as traditional and data‐driven learning methods for manipulating dexterous hands. Additionally, it discusses the challenges faced in terms of the manipulation of multi‐fingered or dexterous hands.

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Section: Imitation Learning (Il)mentioning

confidence: 99%

Review on human‐like robot manipulation using dexterous hands

Sampath

Wang

Wu³

et al. 2023

Cognitive Comp and Systems

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“…According to the means of demonstration, LfD can be implemented by kinesthetic teaching [163] , teleoperation [164,165] , and passive observation [158] . The progress, advantages and applications of LfD have been reviewed in [166].…”

Section: Lfd For Autonomous Ramsmentioning

confidence: 99%

From Teleoperation to Autonomous Robot-assisted Microsurgery: A Survey

Zhang

Fang

et al. 2022

Mach. Intell. Res.

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Robot-assisted microsurgery (RAMS) has many benefits compared to traditional microsurgery. Microsurgical platforms with advanced control strategies, high-quality micro-imaging modalities and micro-sensing systems are worth developing to further enhance the clinical outcomes of RAMS. Within only a few decades, microsurgical robotics has evolved into a rapidly developing research field with increasing attention all over the world. Despite the appreciated benefits, significant challenges remain to be solved. In this review paper, the emerging concepts and achievements of RAMS will be presented. We introduce the development tendency of RAMS from teleoperation to autonomous systems. We highlight the upcoming new research opportunities that require joint efforts from both clinicians and engineers to pursue further outcomes for RAMS in years to come.

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“…In addition, intelligent control methods were employed in the teleoperation to improve the trajectory tracking accuracy, which can ensure the stability of the human-robot skill transfer system (Yang et al, 2019(Yang et al, , 2021a. A comprehensive review on human-robot skill transfer can refer to Si et al (2021c).…”

Section: Teleoperation For Human-robot Skill Transfermentioning

confidence: 99%

“…illustrates the composite layup process through teleoperation and human-robot collaboration. It is challenging to transfer the manipulation skill to robots through teleoperation efficiently and intuitively (Si et al, 2021c).…”

Section: Introductionmentioning

confidence: 99%

A Framework for Composite Layup Skill Learning and Generalizing Through Teleoperation

Wang

et al. 2022

Front. Neurorobot.

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In this article, an impedance control-based framework for human-robot composite layup skill transfer was developed, and the human-in-the-loop mechanism was investigated to achieve human-robot skill transfer. Although there are some works on human-robot skill transfer, it is still difficult to transfer the manipulation skill to robots through teleoperation efficiently and intuitively. In this article, we developed an impedance-based control architecture of telemanipulation in task space for the human-robot skill transfer through teleoperation. This framework not only achieves human-robot skill transfer but also provides a solution to human-robot collaboration through teleoperation. The variable impedance control system enables the compliant interaction between the robot and the environment, smooth transition between different stages. Dynamic movement primitives based learning from demonstration (LfD) is employed to model the human manipulation skills, and the learned skill can be generalized to different tasks and environments, such as the different shapes of components and different orientations of components. The performance of the proposed approach is evaluated on a 7 DoF Franka Panda through the robot-assisted composite layup on different shapes and orientations of the components.

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A review on manipulation skill acquisition through teleoperation‐based learning from demonstration

Cited by 55 publications

References 124 publications

Review on human‐like robot manipulation using dexterous hands

Review on human‐like robot manipulation using dexterous hands

From Teleoperation to Autonomous Robot-assisted Microsurgery: A Survey

A Framework for Composite Layup Skill Learning and Generalizing Through Teleoperation

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