Co-robotic ultrasound tomography: dual arm setup and error analysis

Aalamifar, Fereshteh; Jiang, Dengrong; Zhang, Haichong K.; Cheng, Alexis; Guo, Xiangming; Khurana, Rishabh; Iordachita, Iulian; Boctor, Emad M.

doi:10.1117/12.2084529

Cited by 5 publications

(3 citation statements)

References 10 publications

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“…We have shown, in reference , the feasibility of tomographic image reconstruction given errors in the range of several millimeters. Further improvement can be achieved by looking at the ultrasound signals or by using more robust‐to‐error reconstruction methods.…”

Section: Discussionmentioning

confidence: 97%

Enabling technologies for robot assisted ultrasound tomography

Aalamifar

Khurana

Cheng

et al. 2016

Int J Med Robotics Comput Assist Surg

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Currently available ultrasound (US) tomography systems suggest utilizing cylindrical transducers that can be used for a specific organ. In this paper, our focus is on an alternative way of creating US tomographic images that could be used for other anatomies and more general applications. This system consists of two conventional US probes facing each other while one or several of the transducers in one probe can act as the transmitter and the rest as the receiver. Aligning the two US probes is a challenging task. To address this issue, we propose a robot assisted US tomography system in which one probe is operated freehanded and another by a robotic arm. In this paper, enabling technologies for this system are described. With the current prototype, a reconstruction precision of 4.12, 1.73, and 2.23 mm for the three calibrations, and an overall alignment repeatability in the range of 5-9 mm were achieved. Copyright © 2016 John Wiley & Sons, Ltd.

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Section: Discussionmentioning

confidence: 97%

Enabling technologies for robot assisted ultrasound tomography

Aalamifar

Khurana

Cheng

et al. 2016

Int J Med Robotics Comput Assist Surg

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“…Many recent applications have integrated robotic arms or tracking systems to US imaging [1][2][3][4][5][6][7]. In such systems, US calibration is a necessary task to localize 3D position and orientation of the US image, or US transmitter/receivers in the robot tooltip, tracked marker, or other coordinate frames (called "moving frame," while the fixed frame, e.g., robot base or tracking system, is called "world's frame").…”

Section: Introductionmentioning

confidence: 99%

Robot-assisted automatic ultrasound calibration

et al. 2016

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The submillimeter accuracy requirement of US calibration makes frequent data collections unavoidable. We proposed an automated calibration setup and showed feasibility by implementing it for a robot tooltip to US image calibration. The automated method showed a similar reconstruction precision as well as repeatability compared to the manual method, while the time consumed for data collection was reduced. The automatic method also reduces the burden of data collection for the user. Thus, the automated method can be a viable solution for applications that require frequent calibrations.

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“…(3), the problem of the serial-parallel hybrid robot system [23] is cast as the toolgripper (X), flange-base (Y ) and camera-base (Z) calibrations. The same mathematical modeling also exists in co-robotic ultrasound (US) tomography where two hand-eye and one robot-robot calibrations are needed [1]. However, relatively little work has been done on AXB = Y CZ calibration.…”

Section: Introductionmentioning

confidence: 99%

Probabilistic Approaches to the AXB = YCZ Calibration Problem in Multi-Robot Systems

Goh

Chirikjian

Robotics: Science and Systems XII

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Abstract-In recent years, the topic of multi-robot systems has become very popular. These systems have been demonstrated in various applications, including exploration, construction, and warehouse operations. In order for the whole system to function properly, sensor calibrations such as determining the camera frame relative to the IMU frame are important. Compared to the traditional hand-eye & robot-world calibration, a relatively new problem called the AXB = Y CZ calibration problem arises in the multi-robot scenario, where A, B, C are rigid body transformations measured from sensors and X, Y, Z are unknown transformations to be calibrated. Several solvers have been proposed previously in different application areas that can solve for X, Y and Z simultaneously. However, all of the solvers assume a priori knowledge of the exact correspondence among the data streams {Ai}, {Bi} and {Ci}. While that assumption may be justified in some scenarios, in the application domain of multi-robot systems, which may use ad hoc and asynchronous communication protocols, knowledge of this correspondence generally cannot be assumed. Moreover, the existing methods in the literature require good initial estimates that are not always easy or possible to obtain. In this paper, we propose two probabilistic approaches that can solve the AXB = Y CZ problem without a priori knowledge of the correspondence of the data. In addition, no initial estimates are required for recovering X, Y and Z. These methods are particularly well suited for multi-robot systems, and also apply to other areas of robotics in which AXB = Y CZ arises.

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Co-robotic ultrasound tomography: dual arm setup and error analysis

Cited by 5 publications

References 10 publications

Enabling technologies for robot assisted ultrasound tomography

Enabling technologies for robot assisted ultrasound tomography

Robot-assisted automatic ultrasound calibration

Probabilistic Approaches to the AXB = YCZ Calibration Problem in Multi-Robot Systems

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