Forecasting of Underactuated Robotic Finger Contact Forces by Support Vector Regression Methodology

Jović, Srđan; Danesh, Amir Seyed; Younesi, Emran; Aničić, Obrad; Petković, Dalibor; Shamshirband, Shahaboddin

doi:10.1142/s0218001416590199

Cited by 32 publications

(6 citation statements)

References 22 publications

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“…According to Equation (8), this function estimates external forces from input parameters. We propose two regression methods to obtain L : (i) Support Vector Regression (SVR) [32]; and (ii) Random Forest Regression (RFR) [33].…”

Section: Force Estimation Methodsmentioning

confidence: 99%

Proprioceptive Estimation of Forces Using Underactuated Fingers for Robot-Initiated pHRI

Ballesteros

Pastor

Gómez-de-Gabriel

et al. 2020

Sensors

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In physical Human–Robot Interaction (pHRI), forces exerted by humans need to be estimated to accommodate robot commands to human constraints, preferences, and needs. This paper presents a method for the estimation of the interaction forces between a human and a robot using a gripper with proprioceptive sensing. Specifically, we measure forces exerted by a human limb grabbed by an underactuated gripper in a frontal plane using only the gripper’s own sensors. This is achieved via a regression method, trained with experimental data from the values of the phalanx angles and actuator signals. The proposed method is intended for adaptive shared control in limb manipulation. Although adding force sensors provides better performance, the results obtained are accurate enough for this application. This approach requires no additional hardware: it relies uniquely on the gripper motor feedback—current, position and torque—and joint angles. Also, it is computationally cheap, so processing times are low enough to allow continuous human-adapted pHRI for shared control.

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Section: Force Estimation Methodsmentioning

confidence: 99%

Proprioceptive Estimation of Forces Using Underactuated Fingers for Robot-Initiated pHRI

Ballesteros

Pastor

Gómez-de-Gabriel

et al. 2020

Sensors

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“…Emerging technologies have the potential to drive the development of nations by helping to overcome basic socio-environmental problems (Kumar et al, 2019) through sustainable production systems (König et al, 2018). Some emerging technologies generate transformations in various sectors and areas, such as agribusiness with the genetic improvement of crops, the use of biological pesticides and precision spray drones (King, 2017;Pouvreau et al, 2018) , 2015) and robotic fingers with a sensitive performance for high-risk surgeries (Jovi c et al, 2016); and in engineering using clean technologies for production (e.g. clean concrete) with less greenhouse gas emissions (Wesseling and Vooren, 2017) and renewable energy such as wind energy technologies (Shamshirband et al, 2014).…”

Section: Emerging Technologiesmentioning

confidence: 99%

Dynamic interactions among knowledge management, strategic foresight and emerging technologies

Nascimento

Reichert

Janissek-Muniz³

et al. 2020

JKM

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Purpose This paper aims to discuss the dynamic interactions among knowledge management, strategic foresight and emerging technologies, resulting in a framework that can help companies to shape these interactions for achieving positive outcomes. Design/methodology/approach This conceptual paper is based on prior literature streams, which were interrelated through an abductive research process. This iterative conceptualization approach led to the formation of testable propositions that advance the understanding on the interactions among knowledge management, strategic foresight and emerging technologies. Findings The framework demonstrates the existence of an actions cycle between strategic foresight and knowledge management through a constructivist perspective, where one can improve the other. These interactions can be useful both for the development of emerging technologies and for identifying these innovations in market that can be applied in companies. Hence, all these dynamic interactions do not point to a hegemonic relationship of one construct over the others, but for the value equality among them. Originality/value Although current literature points to the existence of relationships among knowledge management, strategic foresight and emerging technologies, the dynamism inherent in these interactions as well as their positive effects for companies’ results are not properly discussed. This paper fills such a gap and proposes directions for future research.

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“…Evaluation of the complex objective function above a multi-dimensional parameter-space in case of a mesoscopic target consisted of nanoscaled resonators requires a lot of resources; accordingly, a prediction method has been used in present optimization. The applied multilayer absorption law covering method is similar to the SVR or adaptive neurofuzzy predictor methods in the literature, which are used to optimize the efficiency of wind turbines, the quality of laser welding or to predict and control the strength of robotic finger contact forces [38][39][40].…”

Section: Introductionmentioning

confidence: 99%

Comparative Study on the Uniform Energy Deposition Achievable via Optimized Plasmonic Nanoresonator Distributions

et al. 2022

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Plasmonic nanoresonators of core–shell composition and nanorod shape were optimized to tune their absorption cross-section maximum to the central wavelength of a short laser pulse. The number density distribution of randomly located nanoresonators along a laser pulse-length scaled target was numerically optimized to maximize the absorptance with the criterion of minimal absorption difference between neighboring layers illuminated by two counter-propagating laser pulses. Wide Gaussian number density distribution of core–shell nanoparticles and nanorods enabled to improve the absorptance with low standard deviation; however, the energy deposited until the overlap of the two laser pulses exhibited a considerable standard deviation. Successive adjustment resulted in narrower Gaussian number density distributions that made it possible to ensure almost uniform distribution of the deposited energy integrated until the maximal overlap of the two laser pulses. While for core–shell nanoparticles the standard deviation of absorptance could be preserved, for the nanorods it was compromised. Considering the larger and polarization independent absorption cross-section as well as the simultaneously achievable smaller standard deviation of absorptance and deposited energy distribution, the core–shell nanoparticles outperform the nanorods both in optimized and adjusted nanoresonator distributions. Exception is the standard deviation of deposited energy distribution considered for the complete layers that is smaller in the adjusted nanorod distribution. Optimization of both nanoresonator distributions has potential applications, where efficient and uniform energy deposition is crucial, including biomedical applications, phase transitions, and even fusion.

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Forecasting of Underactuated Robotic Finger Contact Forces by Support Vector Regression Methodology

Cited by 32 publications

References 22 publications

Proprioceptive Estimation of Forces Using Underactuated Fingers for Robot-Initiated pHRI

Proprioceptive Estimation of Forces Using Underactuated Fingers for Robot-Initiated pHRI

Dynamic interactions among knowledge management, strategic foresight and emerging technologies

Comparative Study on the Uniform Energy Deposition Achievable via Optimized Plasmonic Nanoresonator Distributions

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