Calibration and External Force Sensing for Soft Robots Using an RGB-D Camera

Zhang, Zhiqing Philippe; Petit, Antoine; Dequidt, Jérémie; Duriez, Christian

doi:10.1109/lra.2019.2903356

Cited by 12 publications

(5 citation statements)

References 26 publications

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“…Given the current camera position t c0 ck with respect to F c,0 , the incremental displacement t c0 ck is computed by solving the optimization problem: min t c ck t c0 ck + t c0 ck 2 which minimizes the absolute camera translation at each step. Considering that t c0 ck = 0 3×2 I 2×2 q (see Section III-A), this optimization problem can also be converted as the following QP problem with an extended optimization variable q. min q 1 2 q T M c q + q T c c (17) where…”

Section: E Endoscope Displacement Limitationmentioning

confidence: 99%

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Image-Guided Control of an Endoscopic Robot for OCT Path Scanning

Zhang

Rosa

Mora

et al. 2021

IEEE Robot. Autom. Lett.

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Optical coherence tomography (OCT) endoscopic catheters provide efficient solutions for the non-invasive scan of malignant tissues in internal human organs. In this paper, we investigate the image-guided control of a robotic flexible endoscopic system equipped with an OCT probe for autonomous tissue scanning. The visual control strategy is achieved by combining the image feedback from both a monocular endoscopic camera (eyeto-hand) and an OCT probe (eye-in-hand). Our control strategy allows the OCT probe to automatically track a trajectory defined by the user on the 2D endoscopic image and keep contact with the scanned surface. The orientation, depth, and endoscopic 2D image position are controlled by solving an optimization problem, which is converted to a quadratic programming problem. For the implementation of the visual control strategy, we also consider visibility constraints and actuators limitations. In addition, a marker-based method to estimate the 3D pose of the continuum robot using only 2D images is proposed based on a Kalman filter and a registration technique. The proposed control strategy is validated using both simulation and laboratory experiments.

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Section: E Endoscope Displacement Limitationmentioning

confidence: 99%

“…T is employed to map the 3D positions to image positions with H i,k = 1 Z i K p 0 where Z i is the depth of ith marker and p 0 is the location of the principal point in the image plane, which are known from camera calibration. Motivated by the work in [17], an optimization-based method is proposed for the registration:…”

Section: A Oct Probe Pose Estimationmentioning

confidence: 99%

Image-Guided Control of an Endoscopic Robot for OCT Path Scanning

Zhang

Rosa

Mora

et al. 2021

IEEE Robot. Autom. Lett.

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“…A coarse model of the object is enough for both deformation tracking and elasticity parameter estimation. Contrary to [5], the remote force estimator does not require a prior knowledge of the elasticity parameter to estimate the deformation forces. The STEPE method can run on inexpensive hardware requiring only a RGB-D sensor and force measurements.…”

Section: B Contributionsmentioning

confidence: 99%

“…However, it is not possible to use them to iteratively update the physical parameters of the object being tracked. Zhang et al used a RGB-D camera to track external forces applied to an object, but with specialized soft robots for the purpose, instead of arbitrary deformable objects [5]. The approach of Petit et al [6] is more suitable for the purpose of deformation tracking using a physics-based model.…”

Section: Introductionmentioning

confidence: 99%

Simultaneous Tracking and Elasticity Parameter Estimation of Deformable Objects

Sengupta

Lagneau

Krupa

et al. 2020

2020 IEEE International Conference on Robotics and Automation (ICRA)

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In this paper, we propose a novel method to simultaneously track the deformation of soft objects and estimate their elasticity parameters. The tracking of the deformable object is performed by combining the visual information captured by a RGB-D sensor with interactive Finite Element Method simulations of the object. The visual information is more particularly used to distort the simulated object. In parallel, the elasticity parameter estimation minimizes the error between the tracked object and a simulated object deformed by the forces that are measured using a force sensor. Once the elasticity parameters are estimated, our tracking algorithm can be used to estimate the deformation forces applied to an object without the use of a force sensor. We validated our method on several soft objects with different shape complexities. Our evaluations show the ability of our method to estimate the elasticity parameters as well as its use to estimate the forces applied to a deformable object without any force sensor. These results open novel perspectives to better track and control deformable objects during robotic manipulations.

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“…Embedding additional sensors to this type of actuator is challenging and makes the system bulky and incompact. Accurate observation of contact detection and grasping behavior by image processing is perplexing task [7], [8]. Moreover, grasp target information i.e size or position remains unidentified due to opaqueness or obstacles between the gripper.…”

Section: Introductionmentioning

confidence: 99%

Evaluating Contact Detection, Size Recognization and Grasping State of an Object using Soft Elastomer Gripper

Jamil¹

2020

IJACSA

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Object handling process of the sensitive or fragile object is critical to preserve its quality. In this domain, soft robotics has gained a lot of attention. However, limitations of detecting contact and grasping behavior is still a challenging task due to the non-linear behavior of soft gripper. Moreover, to regulate grasping behavior, exact real-time contact feedback is a crucial task. To improve the contact detection accuracy a gradient-based algorithm is proposed with the feedback from a simple resistive flex sensor and a pressure sensor. For that purpose firstly, the resistive flex sensor is embedded into the gripper to get the real-time gripper's finger position. Secondly, solenoid valves and pressure sensors are used to control the pneumatic pressure from the pump, and finally, a closed-loop control system is developed for controlling the grasping process. The proposed contact detection algorithm can provide contact feedback with an accuracy of ±3mm, which is implemented to perform the size recognization of the sphere-shaped objects. A real-time experimental setup has been developed which can successfully perform a pick and place of fruits and vegetables.The key benefits of the proposed algorithm are less complexity and better accuracy.

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Calibration and External Force Sensing for Soft Robots Using an RGB-D Camera

Cited by 12 publications

References 26 publications

Image-Guided Control of an Endoscopic Robot for OCT Path Scanning

Image-Guided Control of an Endoscopic Robot for OCT Path Scanning

Simultaneous Tracking and Elasticity Parameter Estimation of Deformable Objects

Evaluating Contact Detection, Size Recognization and Grasping State of an Object using Soft Elastomer Gripper

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