Humanoid Robot Teleoperation with Vibrotactile Based Balancing Feedback

Brygo, Anais; Sarakoglou, Ioannis; Garcia-Hernandez, Nadia; Tsagarakis, Nikos G.

doi:10.1007/978-3-662-44196-1_33

Cited by 13 publications

(11 citation statements)

References 4 publications

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“…For case A, the proposed controller in Eqs. (13) and (14) has α m = 0, σ s = 0, and k m = 0; which means that there is no force feedback applied to the operator. The controller is calibrated in a similar way for case B.…”

Section: Resultsmentioning

confidence: 99%

“…On the other hand, the velocity's component v of the η vector is analyzed, where if f s (14) is applied to the virtual bipedal robot (9), and considering (15), we have:…”

Section: Stability Of Hybrid Real Systemmentioning

confidence: 99%

“…Besides,V 4 from (41) including the virtual robot dynamics (9) as well as the control action f s (14), is given by:…”

Section: A Appendix Given the Functional V (T X)mentioning

confidence: 99%

“…[13] uses the human sensorimotor learning ability to teach a humanoid robot how to compliantly interact with the environment, in ref. [14], an operator was fed back with force signals informing him of the position of the ZMP within the humanoid support polygon, this measurement was used to give the operator an idea of the balance of the robot using a vibrotactile belt for providing cutaneous haptic balance feedback. During the tests performed, the operator is informed trough haptic signals coming from the vibrotactile belt about the stability while commanding the humanoid's hands, and in ref.…”

Section: Introductionmentioning

confidence: 99%

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Delayed Bilateral Teleoperation of the Speed and Turn Angle of a Bipedal Robot

Moya¹,

Slawiñski²,

Mut³

2020

Robotica

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SUMMARY This paper proposes a shared control scheme which aims to achieve a stable control of the speed and turn of a bipedal robot during a delayed bilateral teleoperation. The strategy allows to get a delay-dependent damping value that must be injected to assure a bounded response of the hybrid system, while simultaneously, the human operator receives a force feedback that help him to decrease the synchronism error. Furthermore, a test where a human operator handles the walking of a simulated bipedal robot, to follow a curve path in front of varying time delay, is performed and analyzed.

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Section: Resultsmentioning

confidence: 99%

“…On the other hand, the velocity's component v of the η vector is analyzed, where if f s (14) is applied to the virtual bipedal robot (9), and considering (15), we have:…”

Section: Stability Of Hybrid Real Systemmentioning

confidence: 99%

“…Besides,V 4 from (41) including the virtual robot dynamics (9) as well as the control action f s (14), is given by:…”

Section: A Appendix Given the Functional V (T X)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Delayed Bilateral Teleoperation of the Speed and Turn Angle of a Bipedal Robot

Moya¹,

Slawiñski²,

Mut³

2020

Robotica

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“…This kind of research touches many different areas, among them interaction modalities. Teleoperation can be performed with haptic controllers [19], [4], or by imitation learning with mapping the human motion to a robot [22], [8], [15], [1]. Other ways exist to make human robot interaction more natural, we talk about gesture recognition approach.…”

Section: State Of Artmentioning

confidence: 99%

Gesture recognition for humanoid robot teleoperation

Ajili

Mallem

Didier

2017

2017 26th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN)

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Interactive robotics is a vast and expanding research field. Interactions must be sufficiently natural, with robots having socially acceptable behavior by humans, adaptable to user expectations. Thus allowing easy integration in our daily lives in various fields (science, industry, health ...). Natural interaction during human-robot collaborative action needs suitable interaction techniques. In our paper we develop an online gesture recognition system for natural and intuitive communication between Human and NAO robot. However recognizing meaningful gesture patterns from whole-body gestures is a complex task. That is why we used the Laban Movement Analysis technique to describe high level gestures for NAO teleoperation. The major contributions of the present work is: (1) an efficient preprocessing step based on view invariant human motion, (2) a robust descriptor vector based on Laban Movement Analysis technique to generate compact and informative representations of Human movement, and (3) an online gesture recognition with Hidden Markov Model method was applied to teleoperate NAO based on our proper data base dedicated to the teleoperation of NAO. Our approach was evaluated with two challenging datasets, Microsoft Research Cambridge-12 (MSRC-12) and UTKinect-Action. Experimental results show that our approach outperforms the state-of-the-art methods.

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Human-Humanoid Interaction and Cooperation: a Review

et al. 2021

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Purpose of Review Humanoid robots are versatile platforms with the potential to assist humans in several domains, from education to healthcare, from entertainment to the factory of the future. To find their place into our daily life, where complex interactions and collaborations with humans are expected, their social and physical interaction skills need to be further improved. Recent FindingsThe hallmark of humanoids is their anthropomorphic shape, which facilitates the interaction but at the same time increases the expectations of the human in terms of advanced cooperation capabilities. Cooperation with humans requires an appropriate modeling and real-time estimation of the human state and intention. This information is required both at a high level by the cooperative decision-making policy and at a low level by the interaction controller that implements the physical interaction. Real-time constraints induce simplified models that limit the decision capabilities of the robot during cooperation. SummaryIn this article, we review the current achievements in the context of human-humanoid interaction and cooperation. We report on the cognitive and cooperation skills that the robot needs to help humans achieve their goals, and how these high-level skills translate into the robot's low-level control commands. Finally, we report on the applications of humanoid robots as humans' companions, co-workers, or avatars. Keywords Humanoid robots • Human-robot interaction • CooperationThis article is part of the Topical Collection on Humanoid and Bipedal Robotics

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Humanoid Robot Teleoperation with Vibrotactile Based Balancing Feedback

Cited by 13 publications

References 4 publications

Delayed Bilateral Teleoperation of the Speed and Turn Angle of a Bipedal Robot

Delayed Bilateral Teleoperation of the Speed and Turn Angle of a Bipedal Robot

Gesture recognition for humanoid robot teleoperation

Human-Humanoid Interaction and Cooperation: a Review

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