4-DOF Visual Servoing of a Robotic Flexible Endoscope With a Predefined-Time Convergent and Noise-Immune Adaptive Neural Network

Huang, Yisen; Li, Weibing; Zhang, Xue; Li, Jixiu; Li, Yehui; Sun, Yan; Chiu, Philip Wai Yan; Li, Zheng

doi:10.1109/tmech.2023.3286850

Cited by 10 publications

(3 citation statements)

References 30 publications

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“…This demonstrates the feasibility of target detection through single images. We demonstrate the effect of performing target detection of defects using a neural network [29][30] in fabrics.…”

Section: Tactile Images For Target Detectionmentioning

confidence: 99%

Improving the Representation and Extraction of Contact Information in Vision-based Tactile Sensors Using Continuous Marker Pattern

Li¹,

Zhou²,

Li³

et al. 2023

Preprint

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<p>Tactile perception has been a hot topic of research in robotics. Robots sense the shape, material, distributed force, slip during contact, and use the multi-modal contact information to control grasping and manipulation. For vision-based tactile sensors, the contact representation and extraction determine the quality of the raw tactile information, and therefore serve a significant role in the robot perception system. This article highlights for the first time the importance of raw representation and extraction in visuotactile perception, and proposes a new multicolor CMP method for enhancing the performance of vision-based tactile sensors. Based on the principle of continuous marker pattern (CMP), the multicolor CMP method is optimized in the pattern and algorithm design. Regarding information representation, we present a new type of marker pattern based on RGB triangles and a preferred layout. In terms of information extraction, we propose a series of extraction strategies with the adaptive growing algorithm (AGA) and the spin-search algorithm (SSA) as the cores. The experiments reveal that the multicolor CMP method achieves improved precision and reliability compared to the former CMP method.</p>

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Section: Tactile Images For Target Detectionmentioning

confidence: 99%

Improving the Representation and Extraction of Contact Information in Vision-based Tactile Sensors Using Continuous Marker Pattern

Li¹,

Zhou²,

Li³

et al. 2023

Preprint

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“…It is noteworthy that the integration of visual servoing with neural networks has recently become a research hotspot (Huang et al, 2022 ; Li et al, 2023 ; Cui et al, 2024 ). To ensure the tip of an instrument remains consistently centered in the camera, Huang et al ( 2024 ) proposed an error learning-based sliding mode control, realizing the 4-DOF visual servo control in the robotic flexible endoscope system. The aforementioned research is impressive and offers a novel research perspective.…”

Section: Introductionmentioning

confidence: 99%

Adaptive fuzzy control for tendon-sheath actuated bending-tip system with unknown friction for robotic flexible endoscope

Ren,

Wang,

et al. 2024

Front. Neurosci.

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IntroductionThe tendon-sheath actuated bending-tip system (TAB) has been widely applied to long-distance transmission scenes due to its high maneuverability, safety, and compliance, such as in exoskeleton robots, rescue robots, and surgical robots design. Due to the suitability of operation in a narrow or tortuous environment, TAB has demonstrated great application potential in the area of minimally invasive surgery. However, TAB involves highly non-linear behavior due to hysteresis, creepage, and non-linear friction existing on the tendon routing, which is an enormous challenge for accurate control.MethodsConsidering the difficulties in the precise modeling of non-linearity friction, this paper proposes a novel fuzzy control scheme for the Euler-Lagrange dynamics model of TAB for achieving tracking performance and providing accurate friction compensation. Finally, the asymptotic stability of the closed-loop system is proved theoretically and the effectiveness of the controller is verified by numerical simulation carried out in MATLAB/Simulink.ResultsThe desired angle can be reached quickly within 3 s by adopting the proposed controller without overshoot or oscillation in Tracking Experiment, demonstrating the regulation performance of the proposed control scheme. The proposed method still achieves the desired trajectory rapidly and accurately without steady-state errors in Varying-friction Experiment. The angle errors generated by external disturbances are < 1 deg under the proposed controller, which returns to zero in 2 s in Anti-disturbance Experiment. In contrast, comparative controllers take more time to be steady and are accompanied by oscillating and residual errors in all experiments.DiscussionThe proposed method is model-free control and has no strict requirement for the dynamics model and friction model. It is proved that advanced tracking performance and real-time response can be guaranteed under the presence of unknown bounded non-linear friction and time-varying non-linear dynamics.

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“…Substantial progress has been made in the development and control of multi-DOF flexible endoscopes [ 27 , 28 , 29 , 30 ]. These advancements enhance the FOV and mitigate the limitations found in rigid sensors.…”

Section: Introductionmentioning

confidence: 99%

Endoscope Automation Framework with Hierarchical Control and Interactive Perception for Multi-Tool Tracking in Minimally Invasive Surgery

Fozilov,

Colan,

Davila

et al. 2023

Sensors

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In the context of Minimally Invasive Surgery, surgeons mainly rely on visual feedback during medical operations. In common procedures such as tissue resection, the automation of endoscopic control is crucial yet challenging, particularly due to the interactive dynamics of multi-agent operations and the necessity for real-time adaptation. This paper introduces a novel framework that unites a Hierarchical Quadratic Programming controller with an advanced interactive perception module. This integration addresses the need for adaptive visual field control and robust tool tracking in the operating scene, ensuring that surgeons and assistants have optimal viewpoint throughout the surgical task. The proposed framework handles multiple objectives within predefined thresholds, ensuring efficient tracking even amidst changes in operating backgrounds, varying lighting conditions, and partial occlusions. Empirical validations in scenarios involving single, double, and quadruple tool tracking during tissue resection tasks have underscored the system’s robustness and adaptability. The positive feedback from user studies, coupled with the low cognitive and physical strain reported by surgeons and assistants, highlight the system’s potential for real-world application.

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4-DOF Visual Servoing of a Robotic Flexible Endoscope With a Predefined-Time Convergent and Noise-Immune Adaptive Neural Network

Cited by 10 publications

References 30 publications

Improving the Representation and Extraction of Contact Information in Vision-based Tactile Sensors Using Continuous Marker Pattern

Improving the Representation and Extraction of Contact Information in Vision-based Tactile Sensors Using Continuous Marker Pattern

Adaptive fuzzy control for tendon-sheath actuated bending-tip system with unknown friction for robotic flexible endoscope

Endoscope Automation Framework with Hierarchical Control and Interactive Perception for Multi-Tool Tracking in Minimally Invasive Surgery

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