A Review on Significant Technologies Related to the Robot-Guided Intelligent Bolt Assembly Under Complex or Uncertain Working Conditions

Xu, Jingjing; Zhang, Caixia; Liu, Zhifeng; Pei, Yanhu

doi:10.1109/access.2019.2941918

Cited by 16 publications

(10 citation statements)

References 125 publications

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“…We then choose the input Xr j := X r j ; n r j ∈ 22 for this NN, where X r j is the dynamics-related variables of x r j similar to (4). We design the additional NN similar to (5), which is given as…”

Section: B Data-driven Contact Clusteringmentioning

confidence: 99%

“…W ITH the recent advances of robot hardware and software technologies, many attempts are being made to bring the robots out from research labs to real industrial settings (e.g., [2], [3]). Among those industrial applications, contact-intensive and tight-tolerance robotic assembly tasks (e.g., peg-in-hole assembly [4], bolt-nut assembly [5], snap connector assembly [6]) are ubiquitous, but deemed fairly Fig. 1: Pipelines of the contact simulation framework.…”

Section: Introductionmentioning

confidence: 99%

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Fast and Accurate Data-Driven Simulation Framework for Contact-Intensive Tight-Tolerance Robotic Assembly Tasks

Yoon¹,

Lee²,

Son³

et al. 2022

Preprint

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We propose a novel fast and accurate simulation framework for contact-intensive tight-tolerance robotic assembly tasks. The key components of our framework are as follows: 1) data-driven contact point clustering with a certain variableinput network, which is explicitly trained for simulation accuracy (with real experimental data) and able to accommodate complex/non-convex object shapes; 2) contact force solving, which precisely/robustly enforces physics of contact (i.e., no penetration, Coulomb friction, maximum energy dissipation) with contact mechanics of contact nodes augmented with that of their object; 3) contact detection with a neural network, which is parallelized for each contact point, thus, can be computed very quickly even for complex shape objects with no exhaust pair-wise test; and 4) time integration with PMI (passive mid-point integration [1]), whose discrete-time passivity improves overall simulation accuracy, stability, and speed. We then implement our proposed framework for two widely-encountered/benchmarked contactintensive tight-tolerance tasks, namely, peg-in-hole assembly and bolt-nut assembly, and validate its speed and accuracy against real experimental data. It is worthwhile to mention that our proposed simulation framework is applicable to other general contact-intensive tight-tolerance robotic assembly tasks as well. We also compare its performance with other physics engines and manifest its robustness via haptic rendering of virtual bolting task.

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Section: B Data-driven Contact Clusteringmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Fast and Accurate Data-Driven Simulation Framework for Contact-Intensive Tight-Tolerance Robotic Assembly Tasks

Yoon¹,

Lee²,

Son³

et al. 2022

Preprint

View full text Add to dashboard Cite

show abstract

“…The smart factories of the very near future will see a high presence of industrial robots, not only for large-scale manufacturing as usual but also in versatile production processes, e.g., in SMEs, whose productions are characterized by a strong commitment to continuously adapting to customer requests and meeting the market demands. In this scenario, the possibility of having both manipulators and mobile agents, acting in a coordinated way, sharing the same spaces, and collaborating with the human operators, is very appealing [31]. Multirobot coordination addresses several well-known issues, the correct management of which firstly relies on the proper software and hardware architecture.…”

Section: Future Directions and Open Issuesmentioning

confidence: 99%

Robots in Industry: The Past, Present, and Future of a Growing Collaboration With Humans

Grau

Indri

Bello

et al. 2021

EEE Ind. Electron. Mag.

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“…In the E-skin domain, authors focused on the following: the design and attributes of E-skin (Hammock et al , 2013; Dahiya et al , 2013) and materials used (Yogeswaran et al , 2015); technologies in robot E-skin printing (Wang et al , 2015; Kappassov et al , 2015; Khan and Lorenzelli, 2017); data acquisition techniques from E-skin (Zou et al , 2017; Abhang, 2018; Sappati and Bhadra, 2018); intelligent humanoid robots (Park et al , 2018; Chi et al , 2018); and ML-based humanoid robots (Li et al , 2019; Xu et al , 2019a; Shih et al , 2020), electrical impedance tomography based tactile sensors (Liu et al , 2020). …”

Section: Introductionmentioning

confidence: 99%

“…ML-based humanoid robots (Li et al , 2019; Xu et al , 2019a; Shih et al , 2020), electrical impedance tomography based tactile sensors (Liu et al , 2020).…”

Section: Introductionmentioning

confidence: 99%

Recent trends and role of large area flexible electronics in shape sensing application – a review

Shaik

Rufus

2021

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Purpose This paper aims to review the shape sensing techniques using large area flexible electronics (LAFE). Shape perception of humanoid robots using tactile data is mainly focused. Design/methodology/approach Research papers on different shape sensing methodologies of objects with large area, published in the past 15 years, are reviewed with emphasis on contact-based shape sensors. Fiber optics based shape sensing methodology is discussed for comparison purpose. Findings LAFE-based shape sensors of humanoid robots incorporating advanced computational data handling techniques such as neural networks and machine learning (ML) algorithms are observed to give results with best resolution in 3D shape reconstruction. Research limitations/implications The literature review is limited to shape sensing application either two- or three-dimensional (3D) LAFE. Optical shape sensing is briefly discussed which is widely used for small area. Optical scanners provide the best 3D shape reconstruction in the noncontact-based shape sensing; here this paper focuses only on contact-based shape sensing. Practical implications Contact-based shape sensing using polymer nanocomposites is a very economical solution as compared to optical 3D scanners. Although optical 3D scanners can provide a high resolution and fast scan of the 3D shape of the object, they require line of sight and complex image reconstruction algorithms. Using LAFE larger objects can be scanned with ML and basic electronic circuitory, which reduces the price hugely. Social implications LAFE can be used as a wearable sensor to monitor critical biological parameters. They can be used to detect shape of large body parts and aid in designing prosthetic devices. Tactile sensing in humanoid robots is accomplished by electronic skin of the robot which is a prime example of human–machine interface at workplace. Originality/value This paper reviews a unique feature of LAFE in shape sensing of large area objects. It provides insights from mechanical, electrical, hardware and software perspective in the sensor design. The most suitable approach for large object shape sensing using LAFE is also suggested.

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A Review on Significant Technologies Related to the Robot-Guided Intelligent Bolt Assembly Under Complex or Uncertain Working Conditions

Cited by 16 publications

References 125 publications

Fast and Accurate Data-Driven Simulation Framework for Contact-Intensive Tight-Tolerance Robotic Assembly Tasks

Fast and Accurate Data-Driven Simulation Framework for Contact-Intensive Tight-Tolerance Robotic Assembly Tasks

Robots in Industry: The Past, Present, and Future of a Growing Collaboration With Humans

Recent trends and role of large area flexible electronics in shape sensing application – a review

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