Bayesian Estimation of Human Impedance and Motion Intention for Human–Robot Collaboration

Yu, Xinbo; He, Wei; Li, Yanan; Xue, Chengqian; Li, Jianqiang; Zou, Jianxiao; Yang, Chenguang

doi:10.1109/tcyb.2019.2940276

Cited by 105 publications

(36 citation statements)

References 83 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Might require special or specifically designed tools (costs increment) Require more complex tasks design for recognizing the components Soft-robotics actuators. Pressure sensor integrated grippers 1) Human-robot object simultaneous manipulation 2) Haptic shared teleoperated control 3) Tactile object recognition [98], [99] [100]…”

Section: Requiredmentioning

confidence: 99%

“…In these scenarios, a robot and an operator share a load simultaneously, so proposed strategies are based on force feedback control for object transportation while load stabilization [98]. A similar solution consists of a human impedance and motion intention controller to handle heavy loads [99]. Other approaches are based on applying AI techniques combined with soft robotics actuators to feel and detect objects by touching [102].…”

Section: Requiredmentioning

confidence: 99%

See 1 more Smart Citation

Human-Robot Interaction Review: Challenges and Solutions for Modern Industrial Environments

et al. 2021

View full text Add to dashboard Cite

The demand for collaborative robots is growing in industrial environments due to their versatility and low prices. Thus, more collaborative solutions are emerging for industrial scenarios. However, implementing scenarios where robots work autonomously while synchronizing their operations in a safe industrial environment with shop-floor workers is not easy. To fill the gap existing in the safe implementation of industrial collaborative scenarios, this manuscript presents a review based on five identified challenges that gathers the primary vital aspects to bear in mind while developing applications for them. Thus, a four-level classification is proposed, which collects the identified challenges and the previous developments in the field of human-robot interaction. The five identified challenges pretends to be the missing enabling key for implementing industrial collaborative scenarios in modern industrial plants. Lastly, a discussion and conclusion are exposed to analyze the degree of development in the field and its potential growth.

show abstract

Section: Requiredmentioning

confidence: 99%

Section: Requiredmentioning

confidence: 99%

Human-Robot Interaction Review: Challenges and Solutions for Modern Industrial Environments

et al. 2021

View full text Add to dashboard Cite

show abstract

“…It successfully transfers the human-like stiffness regulation strategy from humans to a Baxter robot, and the framework was validated by designing cucumber-cutting and button-pushing experiments. Yu et al ( 2019 ) then design a human–robot collaborative sawing system based on the sEMG-stiffness mapping to increase the efficiency and produce a smoother wood cutting section area.…”

Section: Introductionmentioning

confidence: 99%

An Improvement of Robot Stiffness-Adaptive Skill Primitive Generalization Using the Surface Electromyography in Human–Robot Collaboration

2021

Self Cite

View full text Add to dashboard Cite

Learning from Demonstration in robotics has proved its efficiency in robot skill learning. The generalization goals of most skill expression models in real scenarios are specified by humans or associated with other perceptual data. Our proposed framework using the Probabilistic Movement Primitives (ProMPs) modeling to resolve the shortcomings of the previous research works; the coupling between stiffness and motion is inherently established in a single model. Such a framework can request a small amount of incomplete observation data to infer the entire skill primitive. It can be used as an intuitive generalization command sending tool to achieve collaboration between humans and robots with human-like stiffness modulation strategies on either side. Experiments (human–robot hand-over, object matching, pick-and-place) were conducted to prove the effectiveness of the work. Myo armband and Leap motion camera are used as surface electromyography (sEMG) signal and motion capture sensors respective in the experiments. Also, the experiments show that the proposed framework strengthened the ability to distinguish actions with similar movements under observation noise by introducing the sEMG signal into the ProMP model. The usage of the mixture model brings possibilities in achieving automation of multiple collaborative tasks.

show abstract

“…Li et al [10] assumed admittance control to deal with a human subject's intention. Yu et al [11] proposed an adaptive impedance control strategy to compensate for dynamic uncertainties.…”

Section: Introductionmentioning

confidence: 99%

Robust Sliding Mode Control for a 2-DOF Lower Limb Exoskeleton Base on Linear Extended State Observer

Chen¹,

Guo²,

Yan³

et al. 2020

Mech. Eng. Sci.

View full text Add to dashboard Cite

For the 2- Degree of Freedom (DOF) lower limb exoskeleton, to ensure the system robustness and dynamic performance, a linear-extended-state-observer-based (LESO) robust sliding mode control is proposed to not only reduce the influence of parametric uncertainties, unmodeled dynamics, and external disturbance but also estimate the unmeasurable real-time joint angular velocity directly. Then, via Lyapunov technology, the stability of the corresponding LESO and controller is proven. The appropriate and reasonable simulation was carried out to verify the effectiveness of the proposed LESO and exoskeleton controller.

show abstract

Bayesian Estimation of Human Impedance and Motion Intention for Human–Robot Collaboration

Abstract: Chenguang (2019) Bayesian estimation of human impedance and motion intention for humanrobot collaboration. IEEE Transactions on Cybernetics. pp. 1-13.

Cited by 105 publications

References 83 publications

Human-Robot Interaction Review: Challenges and Solutions for Modern Industrial Environments

Human-Robot Interaction Review: Challenges and Solutions for Modern Industrial Environments

An Improvement of Robot Stiffness-Adaptive Skill Primitive Generalization Using the Surface Electromyography in Human–Robot Collaboration

Robust Sliding Mode Control for a 2-DOF Lower Limb Exoskeleton Base on Linear Extended State Observer

Contact Info

Product

Resources

About