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Magnetic tracking technology is emerging to provide an occlusion-free tracking scheme for the estimation of full pose of various instruments. This brings substantial benefits for intra-corporeal applications, such as tracking of flexible robots or wireless endoscopic devices, and thus is helpful for further computer-assisted diagnosis, interventions, and surgeries. Towards efficient magnetic tracking, we propose a magnetic localization and orientation system in this paper. By modeling the cylindrical magnet, the magnetic models have been compared and analyzed. Moreover, we present a sensor layout strategy based on grid method and its optimization method for better performance. Based on the magnetic model and the layout optimization results, we have built a sensor array for magnetic positioning. Extensive simulations and experiments have shown the feasibility of the proposed system with the average positional and orientational errors of $1.4 mm$ and 3.4°, respectively.

Magnetically manipulated untethered robot, such as an active wireless capsule endoscope, has shown great potential for controlled inspection inside the gastrointestinal tract. To enable the effective manipulation of the robot, real-time pose (position and orientation) information of the robot must be obtained as an important sensory feedback. Usually, a magnetic tracking method is used to provide the pose information. Due to the magnetic disturbance, a traditional magnetic tracking method cannot work simultaneously with the magnetic manipulation system. In this paper, a simultaneously tracking and navigation method is proposed to realize a closed-loop control of the magnetically manipulated untethered robot. The main approach is to conduct a multi-object tracking of the involved magnetic objects. With the proposed method, real-time pose information can be estimated during the manipulation, and both the tracking and manipulation are carried out by a magnetic manner. Therefore, the mobile navigation of the magnetically manipulated untethered robot can be achieved by using a pre-defined map. Experimental results verified the proposed method, and a mean position error of 1.2 mm for the passive magnet has been obtained.

Magnetic tracking method can achieve wireless tracking and has no line-of-sight problem, therefore it is a good choice to track micro devices inside human body for minimally invasive examination or operation. This method is mainly based on the sensing of the magnetic field generated by small permanent magnets. Usually magnetic dipole model is used to estimate the magnetic field. The disadvantage is that only 5 degree-of-freedom (DoF) pose information can be estimated, with the self rotation information missed. In this paper, we proposed an improved 6D pose detection method, which is based on multiple magnets tracking method. Two magnets with opposite magnetic direction have been combined together to serve as the tracking target. Therefore, we can estimate the missing self rotation information according to the relative movement of these two magnets. Experimental results verified the proposed method. The average position error is 3.0mm and the orientation error is 5.1°.

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.

Image segmentation method based on level set model has wide potential application for its excellent seg-mentation result. However its complex computing restricts its application in video segmentation. In order to improve the speed of image segmentation, this paper presents a new level set initialization method based on Chan-Vese level set model. After a simple iterative, we can separate out the outline of objects. Experiments show that the method is simple and efficient, with good separation effects. The improved Chan-Vese method can be applied in video segmentation.

To satisfy users' diversified requirements, the concept of product design DNA was proposed and became a hot research topic in industrial design. In this experimental study an approach of shape perception is proposed to extract the product design DNA; the relation between shape perception and product design DNA is explored. Taken the gas-cooker's shape design as an example, the novel approaches, cluster analysis and semantic differential (SD) method, were employed. Then four design elements (DNA) of designers' shape perception are explored; the weight factors of these elements are obtained; thereby providing a certain methodology direction for the extraction of product design DNA and for the combination between designers' shape perception and product design DNA in the product design.