A Task Learning Mechanism for the Telerobots

Luo, Jing; Yang, Chenguang; Li, Qiang; Wang, Min

doi:10.1142/s0219843619500099

Cited by 25 publications

(16 citation statements)

References 44 publications

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“…This means that improvement of surgical performance can lead to better outcomes of surgical operations. Surgical performance can be improved through sophisticated remote manipulation of the robot [2][3][4], but surgical feedback also has a positive effect on surgical performance [5]. While manual evaluation methods such as the objective structured assessment of technical skills (OSATS), and the global operative assessment of laparoscopic skills (GOALS) can assess the surgical skills and are beneficial in terms of their improvements, it is both time and labor consuming, because surgeries could last multiple hours [6,7].…”

Section: Introductionmentioning

confidence: 99%

Robust Real-Time Detection of Laparoscopic Instruments in Robot Surgery Using Convolutional Neural Networks with Motion Vector Prediction

Choi

et al. 2019

Applied Sciences

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More than half of post-operative complications can be prevented, and operation performances can be improved based on the feedback gathered from operations or notifications of the risks during operations in real time. However, existing surgical analysis methods are limited, because they involve time-consuming processes and subjective opinions. Therefore, the detection of surgical instruments is necessary for (a) conducting objective analyses, or (b) providing risk notifications associated with a surgical procedure in real time. We propose a new real-time detection algorithm for detection of surgical instruments using convolutional neural networks (CNNs). This algorithm is based on an object detection system YOLO9000 and ensures continuity of detection of the surgical tools in successive imaging frames based on motion vector prediction. This method exhibits a constant performance irrespective of a surgical instrument class, while the mean average precision (mAP) of all the tools is 84.7, with a speed of 38 frames per second (FPS).

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Section: Introductionmentioning

confidence: 99%

Robust Real-Time Detection of Laparoscopic Instruments in Robot Surgery Using Convolutional Neural Networks with Motion Vector Prediction

Choi

et al. 2019

Applied Sciences

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“…in position, and 10 degrees in orientation. Kyrarini et al [14][15][16] presented a framework that permits a robot manipulator to learn how to execute structured tasks from human demonstrations which is automatically segmented into basic movements. The proposed system combined physical human robot interaction with attentional supervision in order to support kinesthetic teaching.…”

Section: Related Workmentioning

confidence: 99%

An Effective Programming by Demonstration Method for Smes’ Industrial Robots

Eissa¹,

Atia²,

Roman³

2020

Journal of Machine Engineering

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Traditional programming methods often require expertise and significant time investment, which does not conform with Small and Medium size Enterprises (SMEs) nature in which High-Mix, Low-Volume (HMLV) orders are usually encountered. In this research, a Programming by Demonstration (PbD) method which aims to reduce the programming time and complexity while keeping a suitable level of execution accuracy is proposed. For this purpose, a special teaching tool is designed and manufactured. The tool has 5-spherical passive markers to indicate the position and orientation along the desired 3D path. An optical tracking system using stereo camera is used to capture the 3D pose of the teaching tool. The capturing algorithm is based on Circle Hough Transform (CHT) and Singular Value Decomposition (SVD). The developed tool and programming method have been tested experimentally. The results show successful capturing of the desired path points with a competitive level of accuracy compared with other methods.

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“…Many problems related to communication and environment issues must to be solved to provide more autonomy to telerobotic systems and to operate the remote robot more easily. [18][19][20] Furthermore, haptic interfaces are devices that enable interaction with virtual or physically remote environments. A haptic interface receives motor commands from the user and generates mechanical signals that stimulate human kinesthetic and touch channels.…”

Section: Introductionmentioning

confidence: 99%

Two-finger exoskeleton with force feedback for a mobile robot teleoperation

Aragón-Martínez

Arias-Montiel

Lugo-González

et al. 2020

International Journal of Advanced Robotic Systems

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In this work, the design, manufacturing, instrumentation, and application of a two-finger exoskeleton with force feedback are presented. The exoskeleton is based on remote center of motion mechanisms in order to avoid mechanical interference with the user’s fingers and is manufactured by three-dimensional printing. The developed exoskeleton is applied in a mobile robot teleoperation by mapping the finger movements in forward and turning commands for the robot. The presence of obstacles detected by the robot is sensed by the user by means of a feedback force. The problem of simultaneously communicating a data acquisition card and the robot hardware by MATLAB ® Simulink® was solved by using an external Wi-Fi module. The result is a lightweight exoskeleton which is able to communicate bidirectionally with a mobile robot by a personal computer for teleoperation tasks. The success of the system implementation is proven by a set of experiments presented in the final part of the article.

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A Task Learning Mechanism for the Telerobots

Cited by 25 publications

References 44 publications

Robust Real-Time Detection of Laparoscopic Instruments in Robot Surgery Using Convolutional Neural Networks with Motion Vector Prediction

Robust Real-Time Detection of Laparoscopic Instruments in Robot Surgery Using Convolutional Neural Networks with Motion Vector Prediction

An Effective Programming by Demonstration Method for Smes’ Industrial Robots

Two-finger exoskeleton with force feedback for a mobile robot teleoperation

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