Manipulability Optimization Control of a Serial Redundant Robot for Robot-assisted Minimally Invasive Surgery

Su, Hang; Li, Shuai; Manivannan, Jagadesh; Bascetta, Luca; Ferrigno, Giancarlo; Momi, Elena De

doi:10.1109/icra.2019.8793676

Cited by 43 publications

(36 citation statements)

References 25 publications

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“…The autonomous laparoscope control is regarded as the principal task and guarantees the safety‐RCM constraint. Therefore, under the null‐space framework and according to the previous studies, it can be concluded that the torque τ R required to ensure the RCM constraint is shown in Equation .

τ_{R} = N_{R} {J_{normalR}}^{T} (α_{R} italicΔd + β_{R} Δ \dot{d}) .

…”

Section: Methodsmentioning

confidence: 90%

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Visual‐based autonomous field of view control of laparoscope with safety‐RCM constraints for semi‐autonomous surgery

Sun

Pan

et al. 2020

Robotics Computer Surgery

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Purpose The surgeon is not timely in direct control of his field of view. Autonomous laparoscope control can provide appropriate surgical field of view and facilitate the intelligent level of surgical robot system. Methods This study explores an autonomous laparoscope control framework for semiautonomous surgery. We propose a novel concept that integrates two forms of Remote Center of Motion (RCM) constraint. We also propose a novel safety‐RCM model to cope with the collision condition. We modify the image Jacobian matrix to realize RCM constraint. The two models constitute a dual‐RCM constraint for robot laparoscope arm. We perform validation of the algorithm with two experiments. Results The experimental results show that the RCM position error can be reduced with the dual‐RCM constraint. Owing to safety‐RCM model, autonomous surgical field of view control could still be realized in case of collision. Conclusion The autonomous laparoscope control could be realized with safety‐RCM and dual‐RCM algorithms.

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τ_{R} = N_{R} {J_{normalR}}^{T} (α_{R} italicΔd + β_{R} Δ \dot{d}) .

…”

Section: Methodsmentioning

confidence: 90%

“…Therefore, under the null-space framework and according to the previous studies, [22][23][24] it can be concluded that the torque τ R required to ensure the RCM constraint is shown in Equation (6).…”

Section: Framework Of Autonomous Laparoscope Controlmentioning

confidence: 91%

Visual‐based autonomous field of view control of laparoscope with safety‐RCM constraints for semi‐autonomous surgery

Sun

Pan

et al. 2020

Robotics Computer Surgery

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show abstract

“…To guarantee control frequency, force sensor, ROS node and OROCOS torque controller were executed on separate computers with UDP communication [41] between each other: the control loop and the sensing ROS node was executed on separate computers, as shown in Figure 8. The system consists of: a seven DoFs LightWeight robotic arm (LWR4+, KUKA, Augsburg, Germany) as slave device.a six-axis force sensor (M8128C6, SRI, Nanning, China) [42] that has the purpose of measuring interaction force between the surgical tool-tip and the environment.…”

Section: Experimental Validation and Resultsmentioning

confidence: 99%

“…a six-axis force sensor (M8128C6, SRI, Nanning, China) [42] that has the purpose of measuring interaction force between the surgical tool-tip and the environment.…”

Section: Experimental Validation and Resultsmentioning

confidence: 99%

Towards Model-Free Tool Dynamic Identification and Calibration Using Multi-Layer Neural Network

et al. 2019

Sensors

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In robot control with physical interaction, like robot-assisted surgery and bilateral teleoperation, the availability of reliable interaction force information has proved to be capable of increasing the control precision and of dealing with the surrounding complex environments. Usually, force sensors are mounted between the end effector of the robot manipulator and the tool for measuring the interaction forces on the tooltip. In this case, the force acquired from the force sensor includes not only the interaction force but also the gravity force of the tool. Hence the tool dynamic identification is required for accurate dynamic simulation and model-based control. Although model-based techniques have already been widely used in traditional robotic arms control, their accuracy is limited due to the lack of specific dynamic models. This work proposes a model-free technique for dynamic identification using multi-layer neural networks (MNN). It utilizes two types of MNN architectures based on both feed-forward networks (FF-MNN) and cascade-forward networks (CF-MNN) to model the tool dynamics. Compared with the model-based technique, i.e., curve fitting (CF), the accuracy of the tool identification is improved. After the identification and calibration, a further demonstration of bilateral teleoperation is presented using a serial robot (LWR4+, KUKA, Germany) and a haptic manipulator (SIGMA 7, Force Dimension, Switzerland). Results demonstrate the promising performance of the model-free tool identification technique using MNN, improving the results provided by model-based methods.

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“…A Kano model analysis is conducted and the TRIZ theory is utilized to redesign a novel rollator for meeting the requirements of the elderly. Compared to the designed rollator in the state of art [3,[37][38][39], the novel rollator is more suitable for elderly users, featured with a simple geometric shape, the adjustable seat, and suitable materials, etc.…”

Section: Resultsmentioning

confidence: 99%

Novel Design and Lateral Stability Tracking Control of a Four-Wheeled Rollator

Zhang

et al. 2019

Applied Sciences

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Design and control of smart rollators have attracted increasing research interests in the past decades. To meet the requirements of the elderly or disabled users, this paper proposes a novel design and tracking control scheme for empowering and assisting natural human mobility with a four-wheeled rollator. Firstly, by integrating the advantages of Kano Model Analysis and the Theory of Inventive Problem Solving (TRIZ), we introduce a novel Kano-TRIZ industrial design method to design and optimize its mechanical structure. The demand and quality characteristics of the clinical rollator are analyzed according to the Kano model. The Quality Function Deployment (QFD) and TRIZ are adopted to integrate industrial product innovations and optimize the function configuration. Furthermore, a lateral stability controller based on Model Predictive Control (MPC) scheme is introduced to achieve good tracking control performance with the lateral deviation and the heading angle deviation. Finally, the feasibility of the design and control method is verified with a simulation study. The simulation results indicate that the proposed algorithm keeps the lateral position error in a reasonable range. In the co-simulation of ADAMS-MATLAB, the trajectory of the rollator is smooth with constrained position error within 0.1 m, the turning angle and speed can achieve stable tracking control within 5 s and the heading angle is accurate and the speed is stable. A compared experiment with MPC and SMC show that MPC controller has faster response, higher tracking accuracy and smoother trajectory on the novel designed rollator. With the increasing demand for rollators in the global market, the methodology proposed in this paper will attract more research and industry interests.

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Manipulability Optimization Control of a Serial Redundant Robot for Robot-assisted Minimally Invasive Surgery

Cited by 43 publications

References 25 publications

Visual‐based autonomous field of view control of laparoscope with safety‐RCM constraints for semi‐autonomous surgery

Visual‐based autonomous field of view control of laparoscope with safety‐RCM constraints for semi‐autonomous surgery

Towards Model-Free Tool Dynamic Identification and Calibration Using Multi-Layer Neural Network

Novel Design and Lateral Stability Tracking Control of a Four-Wheeled Rollator

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