Appearance-Based Gaze Estimator for Natural Interaction Control of Surgical Robots

被引:20
|
作者
Li, Peng [1 ]
Hou, Xuebin [1 ]
Duan, Xingguang [2 ]
Yip, Hiuman [3 ]
Song, Guoli [4 ]
Liu, Yunhui [3 ]
机构
[1] Harbin Inst Technol Shenzhen, Sch Mech Engn & Automat, Shenzhen 518055, Peoples R China
[2] Beijing Inst Technol, Sch Mechatron Engn, Beijing, Peoples R China
[3] Chinese Univ Hong Kong, Dept Mech & Automat Engn, Hong Kong, Peoples R China
[4] Chinese Acad Sci, Shenyang Inst Automat, State Key Lab Robot, Shenyang 110016, Liaoning, Peoples R China
基金
中国国家自然科学基金;
关键词
Deep learning; surgical robot; gaze estimation; convolutional neural network; CALIBRATION;
D O I
10.1109/ACCESS.2019.2900424
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Robots are playing an increasingly important role in modern surgery. However, conventional human-computer interaction methods, such as joystick control and sound control, have some shortcomings, and medical personnel are required to specifically practice operating the robot. We propose a human-computer interaction model based on eye movement with which medical staff can conveniently use their eye movements to control the robot. Our algorithm requires only an RGB camera to perform tasks without requiring expensive eye-tracking devices. Two kinds of eye control modes are designed in this paper. The first type is the pick and place movement, with which the user uses eye gaze to specify the point where the robotic arm is required to move. The second type is user command movement, with which the user can use eye gaze to select the direction in which the user desires the robot to move. The experimental results demonstrate the feasibility and convenience of these two modes of movement.
引用
收藏
页码:25095 / 25110
页数:16
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