Endoscope FOV Autonomous Tracking Method for Robot-Assisted Surgery Considering Pose Control, Hand–Eye Coordination, and Image Definition

Peng, Jianqing; Zhang, Chi; Kang, Liang; Guo, Feng

doi:10.1109/tim.2022.3204086

Cited by 10 publications

(3 citation statements)

References 43 publications

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“…This coupling between the end effector and image sensor complicates matters, making direct homogeneous transformations for hand-eye calibrations unfeasible. Several works address this challenge [ 13 , 14 , 24 , 25 ], but mostly under strong assumptions about detection accuracy and usually in single-tool scenarios.…”

Section: Introductionmentioning

confidence: 99%

“…Different controllers aim primarily at minimizing misorientation error [ 14 , 15 , 24 ]. Recent studies consider multi-objective approaches or speech-based control as additional variables [ 25 , 26 ]. Null-space projection is commonly used to handle multiple constraints but can fall into local minima, particularly when dealing with inequality constraints like joint states.…”

Section: Introductionmentioning

confidence: 99%

“…Most methods focus on single-tool tracking or employ data-driven methodologies [ 15 , 24 ]. Some even integrate surgeon preferences explicitly or via additional interfaces [ 8 , 25 , 26 ]. However, the extension of these methods for multi-tool handling is still an open research area.…”

Section: Introductionmentioning

confidence: 99%

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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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