Positioning and stiffening of an articulated/continuum manipulator for implant delivery in minimally invasive surgery

Tamadon, Izadyar; Huan, Yu; Groot, A.G. de; Menciassi, Arianna; Sinibaldi, Edoardo

doi:10.1002/rcs.2072

Cited by 8 publications

(4 citation statements)

References 31 publications

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“…We introduced the concept of a flexible articulated manipulator with endoscopic vision and flaps on the tip to perform a right minithoracotomy MIAVR via a transaortic approach [26]. In [27], the reported cable-driven articulated manipulator was manually actuated by a technique that minimized cable slackening. Also, the classic constant curvature (CC) modeling was implemented to assess the manipulator's workspace in terms of repeatability and reversibility.…”

Section: A Related Workmentioning

confidence: 99%

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Semiautonomous Robotic Manipulator for Minimally Invasive Aortic Valve Replacement

Tamadon,

Sadati,

Mamone

et al. 2023

IEEE Trans. Robot.

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Aortic valve surgery is the preferred procedure for replacing a damaged valve with an artificial one. The ValveTech robotic platform comprises a flexible articulated manipulator and surgical interface supporting the effective delivery of an artificial valve by teleoperation and endoscopic vision. This article presents our recent work on force-perceptive, safe, semiautonomous navigation of the ValveTech platform prior to valve implantation. First, we present a force observer that transfers forces from the manipulator body and tip to a haptic interface. Second, we demonstrate how hybrid forward/inverse mechanics, together with endoscopic visual servoing, lead to autonomous valve positioning. Benchtop experiments and an artificial phantom quantify the performance of the developed robot controller and navigator. Valves can be autonomously delivered with a 2.0±0.5 mm position error and a minimal misalignment of 3.4±0.9°. The hybrid force/shape observer (FSO) algorithm was able to predict distributed external forces on the articulated manipulator body with an average error of 0.09 N. FSO can also estimate loads on the tip with an average accuracy of 3.3%. The presented system can lead to better patient care, delivery outcome, and surgeon comfort during aortic valve surgery, without requiring sensorization of the robot tip, and therefore obviating miniaturization constraints.

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Section: A Related Workmentioning

confidence: 99%

“…The complete system design has already been presented [27], [28]. Therefore, here it is only briefly summarized by highlighting improvements in the introducer actuation mechanism.…”

Section: B Robot Designmentioning

confidence: 99%

Semiautonomous Robotic Manipulator for Minimally Invasive Aortic Valve Replacement

Tamadon,

Sadati,

Mamone

et al. 2023

IEEE Trans. Robot.

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“…In 1985, Hemami [9] designed a light weight flexible manipulator composed of multiple flexible subsegments, which is one of the earliest publications on TDCRs. Some continuum manipulators adopt the central backbone structure [10,11] and the backbones can be flexible beams, [12] elastomers, [13,14] springs, [15,16] and bellows; [17,18] while the other designs use multiple flexible backbones with a push-pull actuation, which is a modification of the single backbone structure. [19,20] Nevertheless, robotic arms with flexible skeleton structures tend to have poor load capacity.…”

Section: Introductionmentioning

confidence: 99%

Static-to-kinematic modeling and experimental validation of tendon-driven quasi continuum manipulators with nonconstant subsegment stiffness

Zheng 郑,

Ding 丁,

Liu 刘

et al. 2024

Chinese Phys. B

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Continuum robots with high flexibility and compliance have the capability to operate in confined and cluttered environments. To enhance the load capacity while maintaining robot dexterity, we propose a novel non-constant subsegment stiffness (NSS) structure for tendon-driven quasi continuum robots (TDQCR) comprising rigid-flexible coupling subsegments. Aiming at real-time control applications, we present a novel static-to-kinematic modeling approach to gain a comprehensive understanding of the TDQCR model. The analytical subsegment-based kinematics for the multisection manipulator is derived based on screw theory and product of exponentials formula, and the static model considering gravity loading, actuation loading, robot constitutive laws is established. Additionally, the effect of tension attenuation caused by routing channel friction is considered in the robot statics, resulting in improved model accuracy. The root mean square (RMS) error between the outputs of the static model and the experimental system is less than 1.63% of the arm length (0.5 m). By employing the proposed static model, a mapping of bending angles between the configuration space and the subsegment space is established. Furthermore, motion control experiments are conducted on our TDQCR system, and the results demonstrate the effectiveness of the static-to-kinematic model.

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“…For closed-loop control of soft manipulators or arms (Figure 1(a) and (b)), wire encoders have been used to measure the states (Mahl et al, 2014; Kapadia et al, 2014; Tamadon et al, 2020). Other studies have combined the kinematics of the robot with the motion data from cameras or motion capture systems (Hannan and Walker, 2005; Kang et al, 2013; Dalvand et al, 2016; Ansari et al, 2017; Del Giudice et al, 2017; Werner et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

Soft modularized robotic arm for safe human–robot interaction based on visual and proprioceptive feedback

Ku,

Song,

Park

et al. 2024

The International Journal of Robotics Research

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This study proposes a modularized soft robotic arm with integrated sensing of human touches for physical human–robot interactions. The proposed robotic arm is constructed by connecting multiple soft manipulator modules, each of which consists of three bellow-type soft actuators, pneumatic valves, and an on-board sensing and control circuit. By employing stereolithography three-dimensional (3D) printing technique, the bellow actuator is capable of incorporating embedded organogel channels in the thin wall of its body that are used for detecting human touches. The organogel thus serves as a soft interface for recognizing the intentions of the human operators, enabling the robot to interact with them while generating desired motions of the manipulator. In addition to the touch sensors, each manipulator module has compact, soft string sensors for detecting the displacements of the bellow actuators. When combined with an inertial measurement unit (IMU), the manipulator module has a capability of estimating its own pose or orientation internally. We also propose a localization method that allows us to estimate the location of the manipulator module and to acquire the 3D information of the target point in an uncontrolled environment. The proposed method uses only a single depth camera combined with a deep learning model and is thus much simpler than those of conventional motion capture systems that usually require multiple cameras in a controlled environment. Using the feedback information from the internal sensors and camera, we implemented closed-loop control algorithms to carry out tasks of reaching and grasping objects. The manipulator module shows structural robustness and the performance reliability over 5,000 cycles of repeated actuation. It shows a steady-state error and a standard deviation of 0.8 mm and 0.3 mm, respectively, using the proposed localization method and the string sensor data. We demonstrate an application example of human–robot interaction that uses human touches as triggers to pick up and manipulate target objects. The proposed soft robotic arm can be easily installed in a variety of human workspaces, since it has the ability to interact safely with humans, eliminating the need for strict control of the environments for visual perception. We believe that the proposed system has the potential to integrate soft robots into our daily lives.

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Positioning and stiffening of an articulated/continuum manipulator for implant delivery in minimally invasive surgery

Cited by 8 publications

References 31 publications

Semiautonomous Robotic Manipulator for Minimally Invasive Aortic Valve Replacement

Semiautonomous Robotic Manipulator for Minimally Invasive Aortic Valve Replacement

Static-to-kinematic modeling and experimental validation of tendon-driven quasi continuum manipulators with nonconstant subsegment stiffness

Soft modularized robotic arm for safe human–robot interaction based on visual and proprioceptive feedback

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