Continuum robots provide inherent structural compliance with high dexterity to access the surgical target sites along tortuous anatomical paths under constrained environments and enable to perform complex and delicate operations through small incisions in minimally invasive surgery. These advantages enable their broad applications with minimal trauma and make challenging clinical procedures possible with miniaturized instrumentation and high curvilinear access capabilities. However, their inherent deformable designs make it difficult to realize 3-D intraoperative real-time shape sensing to accurately model their shape. Solutions to this limitation can lead themselves to further develop closely associated techniques of closed-loop control, path planning, human-robot interaction, and surgical manipulation safety concerns in minimally invasive surgery. Although extensive model-based research that relies on kinematics and mechanics has been performed, accurate shape sensing of continuum robots remains challenging, particularly in cases of unknown and dynamic payloads. This survey investigates the recent advances in alternative emerging techniques for 3-D shape sensing in this field and focuses on the following categories: fiber-optic-sensor-based, electromagnetic-tracking-based, and intraoperative imaging modality-based shape-reconstruction methods. The limitations of existing technologies and prospects of new technologies are also discussed.

In medical diagnoses and treatments, e.g., endoscopy, dosage transition monitoring, it is often desirable to wirelessly track an object that moves through the human GI tract. In this paper, we propose a magnetic localization and orientation system for such applications. This system uses a small magnet enclosed in the object to serve as excitation source, so it does not require the connection wire and power supply for the excitation signal. When the magnet moves, it establishes a static magnetic field around, whose intensity is related to the magnet's position and orientation. With the magnetic sensors, the magnetic intensities in some predetermined spatial positions can be detected, and the magnet's position and orientation parameters can be computed based on an appropriate algorithm. Here, we propose a real-time tracking system developed by a cubic magnetic sensor array made of Honeywell 3-axis magnetic sensors, HMC1043. Using some efficient software modules and calibration methods, the system can achieve satisfactory tracking accuracy if the cubic sensor array has enough number of 3-axis magnetic sensors. The experimental results show that the average localization error is 1.8 mm.

Wire-driven flexible robots are efficient devices for minimally invasive surgery, since they can work well in complex and confined environments. However, the real-time positional and shape information of the robot cannot be well estimated, especially when there is an unknown payload or force working on the end effector. In this paper, we propose a novel tip tracking and shape sensing method for wire-driven flexible robots. The proposed method is based on the length of each section of the robot as well as the positional and directional information of the distal end of each section of the robot. For each section, an electromagnetic sensor will be mounted at the distal end to estimate the positional and directional information. A reconstruction algorithm, which is based on a three-order Bézier curve, is carried out utilizing the positional and directional information along with the length information of the section. This method provides the advantage of good tracking results and high shape reconstruction accuracy with limited modification to the robot. Compared with other reconstruction methods, no kinematic model is needed for reconstruction. Therefore, this method works well with an unknown payload that applied at the tip of the robot. The feasibility of the proposed method is verified by simulation and experimental results.

Magnetic tracking technology is emerging to provide an occlusion-free tracking scheme for the estimation of full pose (position and orientation) of various instruments. This brings substantial benefits for intracorporeal applications, such as for tracking of flexible or wireless endoscopic devices, and thus is significant for further computer-assisted diagnosis, interventions, and surgeries. Toward efficient magnetic tracking, a 6-D magnetic localization and orientation method is proposed in this paper. An annular permanent magnet is mounted on the exterior surface of a capsule. With a magnetic sensor array, the magnetic field can be measured and the capsule's 3-D location and 3-D orientation information can be estimated based on proposed closed-form analytical model of annular magnet and particle swarm optimization algorithm. Magnetic dipole model and Levenberg-Marquardt algorithm are used to improve the speed and accuracy of estimation. Extensive simulation experiments show that the localization and orientation method works well with good position and orientation accuracy.

The positioning and orientation system consists of three-axis generating coils and three-axis sensor coils in quasi-static magnetic field. The three-axis generating coils are fixed orthogonally and excited by the alternating current (AC) signals with different frequencies. They create the magnetic field that is equivalent to that generated by three orthogonal magnetic dipoles. Using the amplitude and phase information of the sensing signals in the sensor coils, the position and orientation parameters of the sensor coils can be computed by using an appropriate algorithm. In this paper, a novel algorithm is proposed to determine the position of the sensor coil object by some equations directly, so that its position and orientation parameters can be calculated much easier and faster. Based on this method, a system with support circuitry is designed with some special signal acquisition and sampling methods. Especially, a signal extraction (function fitting) method is proposed to pick up the coupling AC signal magnitude of the sensor coils, which simplifies the hardware circuitry and improves the signal acquisition accuracy. The simulation and real experimental results show that the system works satisfactorily with good accuracy.

The wire-driven flexible robot with multiple bending sections is an efficient approach for the minimally invasive surgery and diagnosis. It can function properly in the complicated and restrained environment. One drawback of this technology is that the real-time positional and shape information cannot be well estimated. In order to settle this limitation, we proposed a novel shape estimation method for a wire-driven flexible robot with multiple bending sections in this paper. Each bending section can be controlled independently to deform as an arc with different curvatures. This method is based on the positional and the directional information of limited specific joints on the robot, which can be estimated with an effective positioning method, such as electromagnetic tracking method. The number and the position of these specific joints are only determined by the number of sections. Based on the positional and the directional information, as well as the curve length information, the shape reconstruction algorithm can be carried out by fitting multiple quadratic Bézier curves. Real-time shape sensing platform is built to verify the proposed method. Experimental results show that the method works well and the mean position error is 1.7 mm.