Ultrasound-Based Image Guidance for Robot-Assisted Laparoscopic Radical Prostatectomy: Initial in-vivo Results

Mohareri, Omid; Schneider, Charles L.; Adebar, Troy K.; Yip, Mike C.; Black, Peter C.; Nguan, Christopher; Bergman, Dale; Seroger, Jonathan; DiMaio, Simon P.; Salcudean, Septimiu E.

doi:10.1007/978-3-642-38568-1_5

Cited by 6 publications

(1 citation statement)

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“…The other sectors utilizing the robotics in day-to-day application are automatic surveillance systems initiated for the safety of mankind, gas monitoring and oil pipeline systems for controlling extremely high pressure [9]. For this purpose, small robots are employed which can easily fit inside the pipelines and move around in order to monitor the pipeline issues [10].…”

Section: Introductionmentioning

confidence: 99%

Research on Mobile User Interface for Robot Arm Remote Control in Industrial Application

Balyan

2021

SCPE

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The mobile interfaced robot arms are majorly being used nowadays in order to provide the remote-control applicability for various industrial and manufacturing applications. This article proposes a robotic arm platform for controlling the industrial application. The proposed system includes various modules like a robot arm, a controller module and a remote mobile operating application for visualizing the robot arm angles having real time applicability. Augmented reality (AR) is utilized for robot control WIFI communication and the robot angle information is obtained for varying real time environment. This novel approach incorporated the AR technology into mobile application which allow the real time virtual coordination with physical platform. The feasible trajectories are generated using the proposed methodology and a comparison is made between the desired and real trajectory paths. The simulation results are obtained for various assessment indicators and effectual outcomes are achieved with 98.03% accuracy value and 0.185, 0.180 of error and loss values for training phase. The accuracy value of 97.65% is achieved for testing phase with corresponding 0.209 and 0.190 minimum error and loss values. The proposed platform provides the feasible and reliable outcomes in the real time environment for real time manufacturing industry applications.

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Section: Introductionmentioning

confidence: 99%