Automatic positioning system of medical service robot based on binocular vision

Author(s):  
Haowei Ma
2021 ◽  
Vol 1748 ◽  
pp. 042011
Author(s):  
Xing Zhang ◽  
Qiaoming Gao ◽  
Dong Pan ◽  
Peng Cheng Cao ◽  
Dong Hui Huang

2005 ◽  
Vol 102 (Special_Supplement) ◽  
pp. 25-28 ◽  
Author(s):  
Daniela Tlachacova ◽  
Michal Schmitt ◽  
Josef Novotny ◽  
Josef Novotny ◽  
Mustafa Majali ◽  
...  

Object. The authors sought to compare the quality of treatment planning, radiation protection, and the time taken for treatment in the Leksell gamma knife model B with that using the model C Automatic Positioning System (APS). Methods. Data were obtained in 463 patients treated with the B model and 518 patients treated with the C model. Data were analyzed in patients in whom the following diagnoses had been made: vestibular schwannoma, pituitary adenoma, meningioma, solitary metastasis, and other benign and malignant solitary tumors. Patients with arteriovenous malformations, ocular lesions, and functional diagnoses were excluded from this study. Conclusions. With the C model there was a better conformity for most treated targets, such as vestibular schwannomas (p = 0.005) and meningiomas (p = 0.015). The level of radiation exposures to personnel was significantly decreased when using the model C (p < 0.001). There was no significant difference in radiation exposure of extracranial structures for the same number of shots in patients treated by both models. The mean time saved using the C model with the APS was 41 minutes per treatment. It would seem that the gamma knife model C permits better dose conformity, shorter treatment times, and less radiation exposure to personnel.


Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Xin Zhang ◽  
Jiehao Li ◽  
Wen Qi ◽  
Xuanyi Zhou ◽  
Yingbai Hu ◽  
...  

Recently, as a highly infectious disease of novel coronavirus (COVID-19) has swept the globe, more and more patients need to be isolated in the rooms of the hospitals, so how to deliver the meals or drugs to these infectious patients is the urgent work. It is a reliable and effective method to transport medical supplies or meals to patients using robots, but how to teach the robot to the destination and to enter the door like a human is an exciting task. In this paper, a novel human-like control framework for the mobile medical service robot is considered, where a Kinect sensor is used to manage human activity recognition to generate a designed teaching trajectory. Meanwhile, the learning technique of dynamic movement primitives (DMP) with the Gaussian mixture model (GMM) is applied to transfer the skill from humans to robots. A neural-based model predictive tracking controller is implemented to follow the teaching trajectory. Finally, some demonstrations are carried out in a hospital room to illustrate the superiority and effectiveness of the developed framework.


2020 ◽  
Vol 48 (6) ◽  
pp. 1566-1571
Author(s):  
Daniele Aprile ◽  
Piero Agostinetti ◽  
Sylvestre Denizeau ◽  
Giuseppe Chitarin

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