Preoperative planning for a multi-arm robot-assisted minimally invasive surgery system

Du, Zhijiang; Wang, Wei; Wang, Weidong; Dong, Wei

doi:10.1177/0037549717719336

Cited by 15 publications

(8 citation statements)

References 33 publications

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“…In addition, the paper used global isotropy index and cooperation capability index as two objective functions to reflect the dexterity of the robot arm and the cooperation performance of the multi-arm, respectively. Du [23] proposed an isotropy evaluation index based on the coefficient of variation that represents the ratio of the standard deviation σ to the mean μ. It combines all the singular values and indicates the mean and the volatility of all the data.…”

Section: Contraints and Optimization Objectivesmentioning

confidence: 99%

Preoperative Planning Algorithm for Robot-Assisted Minimally Invasive Cholecystectomy Combined With Appendectomy

et al. 2020

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Preoperative planning for robot-assisted minimally invasive surgery is critical stage. Recently, many studies focus on the preoperative planning of the robot-assisted minimally invasive single-site surgery. However, the preoperative planning for the robot-assisted minimally invasive combined surgery based on the optimization algorithm has not been reported. In order to improve the dexterity and coordination of the manipulators in the surgical areas and to reduce the preoperative adjustment time for the combined surgery, this paper proposes a preoperative planning algorithm based on the non-dominated sorting genetic algorithm II (NSGA-II) for robot-assisted minimally invasive Cholecystectomy combined with Appendectomy (RAMICA). The preoperative planning algorithm simultaneously optimizes the entry ports and configurations of the manipulators. The optimization objective functions of the preoperative planning algorithm consist of a novel global dexterity index (GDI) based on the coefficient of variation and the coordination index (CI) that reflects hand-eye coordination and instrument coordination. The constraints of the preoperative planning algorithm include the port placement constraint and the non-collision constraint. The preoperative planning scheme based on the optimization algorithm are verified by comparative simulations to provide the better dexterity and coordination of the manipulators. Finally, the contrast experiments are carried out to demonstrate the effectiveness and superiority of the preoperative planning scheme obtained by the optimization algorithm. INDEX TERMS Preoperative planning, robot-assisted minimally invasive surgery, Cholecystectomy combined with Appendectomy, NSGA-II optimization algorithm.

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Section: Contraints and Optimization Objectivesmentioning

confidence: 99%

Preoperative Planning Algorithm for Robot-Assisted Minimally Invasive Cholecystectomy Combined With Appendectomy

et al. 2020

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“…The same year, Du et al used the algorithm NSGA-II to carry out a preoperative planning robot-assisted minimally invasive surgery system. In this work was simultaneously optimized the incision placement and the initial pose for the manipulator [28]. Figure 4 illustrates the general operation of the candidate trajectory generation process, where the sets E (entry points region) and G (target points region) are the input for the generation and selection of trajectories process, as a result this process gives all possible trajectories.…”

Section: Proposed Trajectories Selection Algorithmmentioning

confidence: 99%

Novel Risk Assessment Methodology for Keyhole Neurosurgery with Genetic Algorithm for Trajectory Planning

Villanueva-Naquid¹,

Soubervielle‐Montalvo²,

Rm³

et al. 2018

Preprint

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Keyhole neurosurgery implies reaching a target area inside the brain through an entry point specified by the neurosurgeon. In order to avoid complications, a risk assessment procedure must be done to establish the minimum risk trajectory from the entry point to the target area. The neurosurgeon establishes the risk values for the brain structure according to the type of intervention. The preset brain structure risk value is used to assess the risk value for each voxel of the brain. This paper proposes an improved risk assessment methodology based on the sum of N maximum risk values for each voxel. Then, risk assessment for a trajectory is done by adding the risk of all voxels that are part of the path. The safest trajectory is defined as the trajectory with the lower risk. Our proposed search trajectory methodology includes a Genetic Algorithm (GA) for finding the safest trajectories. The use of a GA drastically reduces the number of trajectories to analyze, speeding up the planning procedure. The achieved results were qualified by expert neurosurgeons as satisfactory. Our proposed method allows neurosurgeons to calibrate the surgical planning system by allowing them to establish the risk brain structure and the risk value for each structure.

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“…In [ 1 , 28 , 31 ], the robotic arm and surgical instruments studied in this paper are introduced. The robotic arm carried a certain surgical instrument shown in Figure 3 .…”

Section: The Position Compensation Schemementioning

confidence: 99%

A Novel Position Compensation Scheme for Cable-Pulley Mechanisms Used in Laparoscopic Surgical Robots

Liang

Wang

et al. 2017

Sensors

Self Cite

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The tendon driven mechanism using a cable and pulley to transmit power is adopted by many surgical robots. However, backlash hysteresis objectively exists in cable-pulley mechanisms, and this nonlinear problem is a great challenge in precise position control during the surgical procedure. Previous studies mainly focused on the transmission characteristics of the cable-driven system and constructed transmission models under particular assumptions to solve nonlinear problems. However, these approaches are limited because the modeling process is complex and the transmission models lack general applicability. This paper presents a novel position compensation control scheme to reduce the impact of backlash hysteresis on the positioning accuracy of surgical robots’ end-effectors. In this paper, a position compensation scheme using a support vector machine based on feedforward control is presented to reduce the position tracking error. To validate the proposed approach, experimental validations are conducted on our cable-pulley system and comparative experiments are carried out. The results show remarkable improvements in the performance of reducing the positioning error for the use of the proposed scheme.

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Preoperative planning for a multi-arm robot-assisted minimally invasive surgery system

Cited by 15 publications

References 33 publications

Preoperative Planning Algorithm for Robot-Assisted Minimally Invasive Cholecystectomy Combined With Appendectomy

Preoperative Planning Algorithm for Robot-Assisted Minimally Invasive Cholecystectomy Combined With Appendectomy

Novel Risk Assessment Methodology for Keyhole Neurosurgery with Genetic Algorithm for Trajectory Planning

A Novel Position Compensation Scheme for Cable-Pulley Mechanisms Used in Laparoscopic Surgical Robots

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