3-D Reconstruction and Measurement System Based on Multimobile Robot Machine Vision

Moemen, Moemen Y.; Elghamrawy, Haidy; Givigi, Sidney N.; Noureldin, Aboelmagd

doi:10.1109/tim.2020.3026719

Cited by 22 publications

(9 citation statements)

References 28 publications

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“…C AMERA network is widely used to fulfill various visual tasks in industry, such as surveillance [1], [2], industrial inspection [3], motion capture [4], 3-D reconstruction [5], [6] and so on. Among these implementations, visual coverage is a crucial problem, whose objective is to achieve environmental perception via deploying the visual sensors in 2-D [7]- [9] or 3-D areas [10]- [12].…”

Section: Introductionmentioning

confidence: 99%

Coverage Optimization of Camera Network for Continuous Deformable Object

Li¹,

Chen²,

Chai³

2022

Preprint

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Section: Introductionmentioning

confidence: 99%

Coverage Optimization of Camera Network for Continuous Deformable Object

Li¹,

Chen²,

Chai³

2022

Preprint

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“…This setup can also be used as a stabilization system for flappingwings [29], obstacle avoidance for UAVs [30], and flight maneuvering tracking [31]. Vision-based control can also benefit truss-based morphing mechanisms with a large number of actuators [32], which is an active research field in the robotics field [33], [34].…”

Section: Introductionmentioning

confidence: 99%

Vision-Based Nonlinear Incremental Control for a Morphing Wing With Mechanical Imperfections

Sun

Mkhoyan

Kampen

et al. 2022

IEEE Trans. Aerosp. Electron. Syst.

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Morphing structures have acquired much attention in the aerospace community because they enable an aircraft to actively adapt its shape during flight, leading to fewer emissions and fuel consumption. Researchers have designed, manufactured, and tested a morphing wing named SmartX-Alpha, which can actively alleviate loads while achieving the optimal lift distribution. However, the widely existing mechanical imperfections can degrade the performance of the morphing wing and even lead to instabilities. To tackle these issues, this article proposes a vision-based adaptive control approach to actively compensate for mechanical imperfections. In this approach, an incremental model is constructed online to identify the system dynamics using servo commands and vision measurements, and then, nonlinear dynamic inversion control is applied based on the identified model. This data-driven control approach with visual feedback has been validated by real-world experiments on the SmartX-Alpha. The results demonstrate that the vision-based system combined with the proposed control methodology can actively compensate for mechanical imperfections with minimal adjustments to the actual system design. Compared to a controller that only uses a feedforward input-output mapping, this proposed approach improves the system performance and decreases the tracking errors by more than 62% despite disturbances. The results collectively demonstrate the effectiveness of Manuscript

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“…Both can individually achieve tasks such as object recognition, [ 9,10 ] human behavior analysis, [ 11,12 ] and 3D information reconstruction. [ 13,14 ] However, as the knowledge acquired by using only the one or the other is still limited, they do not perform well when completing complex tasks. For example, it is challenging to identify large objects solely using tactile sensing.…”

Section: Introductionmentioning

confidence: 99%

Tactile and Vision Perception for Intelligent Humanoids

Gao

Dai

Nathan

2021

Advanced Intelligent Systems

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Touch and vision perception are two important functions humans use to interact with the real world. To mimic human‐like abilities, tactile‐ and visual‐sensing‐based intelligent humanoids have emerged and are going through a fast phase of development. Studies have demonstrated that the combination of tactile and visual information not only enables humanoids to better learn the environment, but also allows them to have pseudocognitive ability. Being a new and rapidly developing field of research, a significant growth in articles reporting different aspects of sensing and related machine learning is being witnessed. To help readers comprehensively understand the fundamentals and insights, and the current state of the art, this review is compiled to explain the working mechanisms of tactile and visual sensing, introduce the application of intelligent humanoids in diverse scenarios, discuss current challenges, and predict future trends.

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3-D Reconstruction and Measurement System Based on Multimobile Robot Machine Vision

Cited by 22 publications

References 28 publications

Coverage Optimization of Camera Network for Continuous Deformable Object

Coverage Optimization of Camera Network for Continuous Deformable Object

Vision-Based Nonlinear Incremental Control for a Morphing Wing With Mechanical Imperfections

Tactile and Vision Perception for Intelligent Humanoids

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