Flexible manipulator enables curvilinear accessibility through small incisions or natural orifices for minimally invasive surgery and diagnosis, which makes it a good choice for minimally invasive surgery. In order to control the robot precisely and safely, the real-time position and shape information of the robot need to be measured well. In this paper, we propose a magnetic tracking based tip pose and shape detection method for wire driven flexible robots. A permanent magnet is mounted at the distal end of the robot. Its magnetic field can be sensed with a sensor array. Therefore, position and orientation of the tip can be estimated utilizing the tracking method. A shape sensing algorithm is then carried out to estimate the real-time shape based on the tip pose. With the tip pose and shape display in the reconstructed visual environment, navigation can be achieved. This method provides the advantages that no sensors are needed to mount on the robot and has no line-of-sight problem. Experimental results verified the feasibility of the proposed method. A navigation error of 1.9mm is achieved.

Composed of multi-section precurved tubes, continuous concentric-tube robot(CTR) has the potential of reaching surgical target during minimally invasive surgeries. Since concentric tubes are made of super-elastic nickel-titanium alloy, they can present different shapes when they extend and rotate with respect to each other. Compared to traditional surgical robots, CTR is superior in small size and flexible bending so that it can work in tiny space and adapt well to non-structural environment with multiple obstacles. In this paper, we proposed a CTR with 38cm in length and 1.85kg in weight which is assembled on a two-freedom platform to enable surgeons to perform various surgeries. Structure design of CTR and an image-guided algorithm are described in detail. For the propose of controlling robot to reach the target more precisely, a single camera is mounted at the tip of concentric tubes which can estimate the mapping between image plane and robotic joint space. This paper presents a model-less method based on Kalman filter to online estimate image Jacobian matrix, therefore robot is capable of capturing the target accurately accompanied by position changes on image plane. Experimental demonstration is also presented in this paper to verify the proposed method.

Wire-driven flexible robot can work in confined and complex environments, so that it has been studied for minimally invasive surgery. On account of guarantee the accuracy and effectiveness of the robot, the real-time tip pose and shape information of the robot should be measured. In this paper, a tip pose and shape detection method based on magnetic tracking for the wire-driven flexible robot is presented. This method makes use of the magnetism of a permanent magnet that mounted on the terminal of the robot to obtain the tip pose. On the basis of the tip pose, a shape reconstruction algorithm based on the three order Bézier curve is used to estimate the real-time shape of the robot. In accordance with the tip position and the mapped environment, the navigation of the robot still can be achieved without the need for sensors in the absence of the line of sight environment. To evaluate the feasibility, a experiment has been carried out and a navigation error is about 1.1mm.

Composed of multiple precurved tubes, continuous concentric-tube robot (CTR) has the potential of reaching surgical target during minimally invasive surgeries. Since concentric tubes are made of super-elastic nickel-titanium alloy, they can present different shapes when they extend and rotate with respect to each other. Compared to traditional surgical robots, CTR is superior in small size and flexible bending so that it can work in tiny space and adapt well to non-structural environment with multiple obstacles. However, real-time shape information of the robot cannot be well estimated especially when it bears unknown external forces in confined environment Therefore, shape sensing and position tracking are important in clinical surgery. In this paper, we present a multi-magnet tracking based robot joint tracing and shape sensing method. Small magnets are mounted at the end of each joint whose position and orientation information can be estimated by a magnetic positioning system. A shape reconstruction algorithm is then carried out based on three order Bézier curves to fit the shape of CTR. Experimental results with a mean error of 1.38mm verified that the proposed shape reconstruction has a better accuracy than the kinematic model when undertaking payload.