Project Goals
As a typical minimally invasive surgery, transoral surgery brings to patients significant benefits such as decreased intra-operative blood loss, less post-operative complication morbidity, shorter hospitalization length and recovery period. Flexible surgical robot (such as tendon/wire/cable-driven robot and concentric tube robot) is an efficient device for transoral inspection and diagnosis. It can work well in complicated and confined environments. One drawback of this method is that the real time tip position and shape information cannot be well estimated, especially when there is payload on the end effector. To address these challenges, we focus on a novel tip tracking and shape sensing method for the flexible surgical robot.
Approaches
The proposed method is based on the positional and directional information of limited specific joints of the robot, which are estimated with an electromagnetic tracking system. Electromagnetic sensors have been mounted in the tip of the robot to provide the tip position and direction information. Based on the section number of the robot, some other sensors will be mounted in the specific position of the robot to realize the shape sensing. The shape sensing method is based on multi quadratic Bézier curves.
Fig.1 Electromagnetic tracking method.
The electromagnetic tracking method is shown in Fig.1. A uniaxial sensing coil is used as the target and sensing the magnetic field that generated by the six transmitting coils. These six coils are stimulated sequentially. The position and orientation information of the sensing coil can then be estimated based on the sensing signals.
Fig.2 Shape sensing method.
Fig.2 shows the shape sensing method for multi-section flexible by using multi quadratic Bézier curves. For a N sections robot, ⌈N/2⌉ electromagnetic sensors will be mounted in the tail of the (N-2k)th section, where 0≤k<n/2. Therefore, by utilizing the positional and directional information of the sensors, each section can be reconstructed based on a quadratic Bezier curve. Compared to the image based method, this method is easy to setup; compared to the FBG based method, curvature information is not used and fewer sensors are needed in the proposed method.
Results and Remarks
Fig.3 Two Uniaxial electromagnetic sensing coils are mounted in both ends of the device.
We have applied the method on a 10-joints wire-driven flexible robot. As shown in Fig.3, two uniaxial electromagnetic sensors (Aurora Shielded and Isolated 5DOF Sensor, 0.9* 12mm) have been mounted on both ends of the robot. Fig.4 shows the average errors of the experimental results of each S shape curve reconstruction in the experiments. The whole average error is 1.4mm.
We have also applied the method on a two-section concentric tube. As shown in Fig.5, a uniaxial sensor has been mounted in the tip of the robot. The tracking results can be seen in the video.
Fig.4 Experimental results for the wire-driven flexible robot.
Fig.5 Tip tracking and shape sensing for concentric tube robot. The result can be seen in the video below.
The primary contributions of our work are summarized as follows:
1)A shape sensing method based on Bézier curve fitting and electromagnetic tracking is proposed. This method needs only the positional and directional information of some specific position of the curved robot.
2)Only limited sensors are needed, and thus very few modifications are required on the robot.
3)Compared with other methods, the proposed method is easy to set up and has a good accuracy.
People Involved
Staff: Shuang Song, Zheng Li
Investigators: Hongliang Ren, Haoyong Yu
Video
Publications
[1] Shuang Song, Wan Qiao, Baopu Li, Chao Hu, Hongliang Ren and Max Meng. “An Efficient Magnetic Tracking Method Using Uniaxial Sensing Coil”. Magnetics, IEEE Transactions on, 2014. 50(1), Article#: 4003707
[2] Shuang Song, Hongliang Ren and Haoyong Yu. “An Improved Magnetic Tracking Method using Rotating Uniaxial Coil with Sparse Points and Closed Form Analytic Solution”. IEEE Sensors Journal, 14(10): 3585-3592, 2014
[3] Shuang Song, Baopu Li, Wan Qiao, Chao Hu, Hongliang Ren, Haoyong Yu, Qi Zhang, Max Q.-H. Meng and Guoqing Xu. “6-D Magnetic Localization and Orientation Method for an Annular Magnet Based on a Closed-Form Analytical Model”. IEEE Transactions on Magnetics. 2014, 50(9), Article#: 5000411
