Autonomous Data-Driven Manipulation of Unknown Anisotropic Deformable Tissues Using Unmodelled Continuum Manipulators

Alambeigi, Farshid; Wang, Zerui; Hegeman, Rachel; Liu, Yunhui; Armand, Mehran

doi:10.1109/lra.2018.2888896

Cited by 58 publications

(45 citation statements)

References 33 publications

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“…However, one of the main challenges is the intra-operative real-time identification of tissue parameters describing the elasticity and stiffness of a given surface. Recently, 3D displacements and kinematic data were combined to evaluate the deformation through optimization techniques in [111,112]. Results demonstrated the system ability to evaluate the parameters in real-time, but quantitative assessments of the performances are not available.…”

Section: Tissue Modellingmentioning

confidence: 99%

Autonomy in Surgical Robotics

Attanasio

Scaglioni

Momi

et al. 2021

Annu. Rev. Control Robot. Auton. Syst.

137

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This review examines the dichotomy between automatic and autonomous behaviors in surgical robots, maps the possible levels of autonomy of these robots, and describes the primary enabling technologies that are driving research in this field. It is organized in five main sections that cover increasing levels of autonomy. At level 0, where the bulk of commercial platforms are, the robot has no decision autonomy. At level 1, the robot can provide cognitive and physical assistance to the surgeon, while at level 2, it can autonomously perform a surgical task. Level 3 comes with conditional autonomy, enabling the robot to plan a task and update planning during execution. Finally, robots at level 4 can plan and execute a sequence of surgical tasks autonomously. Expected final online publication date for the Annual Review of Control, Robotics, and Autonomous Systems, Volume 4 is May 3, 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

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Section: Tissue Modellingmentioning

confidence: 99%

Autonomy in Surgical Robotics

Attanasio

Scaglioni

Momi

et al. 2021

Annu. Rev. Control Robot. Auton. Syst.

137

View full text Add to dashboard Cite

show abstract

“…The latter approach is concerned with the estimation of force on the basis of gathered data from other sensors, which facilitates the selection of sensor type and placement. It should be noted that in the case of load carrying maneuver, different kinematics and dynamics may be achieved compared to free motion [32]. Hence, the effect of force should be involved.…”

Section: Ik/id and Path Trackingmentioning

confidence: 99%

Dynamics and path tracking of continuum robotic arms using data-driven identification tools

Parvaresh

Moosavian

2021

Robotica

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In this paper, forward/inverse dynamics of a continuum robotic arm is developed using a data-driven approach, which could tackle uncertainties and extreme nonlinearities to obtain reliable solutions. By establishing a direct mapping between the actuator and task spaces, the unnecessary mappings of actuator-to-configuration then configuration-to-task are eliminated, to reduce extra computational cost. The proposed approach is validated through simulation (based on Cosserat rod theory) and experimental tests on RoboArm. Next, path tracking in the presence/absence of obstacles as well as load carrying maneuver are investigated. Finally, the obtained results concerning repeatability, scalability, and disturbance rejection performance of the approach are discussed.

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“…Similar features are used in [8] to servo the shape of a flexible cable with dual-arm manipulation. [10] and [11] servo a soft tissue under small deformations controlling a set of less than five image points. The features controlled in these approaches are a reduced representation of the object's geometry and do not encode its full 3D shape.…”

Section: B Monocular Shape Servoing Schemesmentioning

confidence: 99%

“…[26] reviewed model-based deformable object manipulation approaches, which generally address planning and open-loop control. Most of the methods that address shape servoing [1], [7]- [11], [19], [21], [22] are, instead, model-free. They control shape features using an estimation of a deformation Jacobian from sensor measurements.…”

Section: Model-based Vs Model-free Deformable Manipulationmentioning

confidence: 99%

Monocular Visual Shape Tracking and Servoing for Isometrically Deforming Objects

Aranda

Ramón

Mezouar

et al. 2020

2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

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We address the monocular visual shape servoing problem. This pushes the challenging visual servoing problem one step further from rigid object manipulation towards deformable object manipulation. Explicitly, it implies deforming the object towards a desired shape in 3D space by robots using monocular 2D vision. We specifically concentrate on a scheme capable of controlling large isometric deformations. Two important open subproblems arise for implementing such a scheme. (P1) Since it is concerned with large deformations, perception requires tracking the deformable object's 3D shape from monocular 2D images which is a severely underconstrained problem. (P2) Since rigid robots have fewer degrees of freedom than a deformable object, the shape control becomes underactuated. We propose a template-based shape servoing scheme in which we solve these two problems. The template allows us to both infer the object's shape using an improved Shape-from-Template algorithm and steer the object's deformation by means of the robots' movements. We validate the scheme via simulations and real experiments.

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Autonomous Data-Driven Manipulation of Unknown Anisotropic Deformable Tissues Using Unmodelled Continuum Manipulators

Cited by 58 publications

References 33 publications

Autonomy in Surgical Robotics

Autonomy in Surgical Robotics

Dynamics and path tracking of continuum robotic arms using data-driven identification tools

Monocular Visual Shape Tracking and Servoing for Isometrically Deforming Objects

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