A Novel Passive Magnetic Localization Wearable System for Wireless Capsule Endoscopy

Although capsule endoscopy is already used for diagnosis of the gastrointestinal tract, a method to precisely localize the capsules, important for accurate diagnosis, is lacking. Static magnetic localization is a promising solution for that purpose. In this paper, the simulation of a differential static magnetic localization system with dynamic geomagnetic compensation was optimized. First, a convergence-test for the position and orientation errors as a function of the dimension of the computational domain was conducted. Subsequently, the diameter-to-length ratio of a permanent magnet was varied and the corresponding position and orientation errors, as well as the mean magnetic flux density measured at the sensor positions, were compared. The results revealed that for a computational domain radius of 800 mm, the position and orientation errors converged to less than 0.1 mm and 0.1°, respectively. The position and orientation errors were also of that order, even with the smallest permanent magnet employed in the study. Furthermore, the mean magnetic flux density measured at the sensors of the proposed magnetic localization system would be detectable using state-of-the-art magnetometers. It is concluded that the differential localization method is also feasible for small permanent magnets, which is especially important considering the limited space within endoscopy capsules.

To estimate influence of velocity on kinematic accuracy for a cross-linked Stewart type Parallel Machine Tool, position and orientation errors of the moving tool platform are researched. Based on rigid body dynamics, inertial and friction forces and moments are considered. Firstly, analytical expression of driving force is derived for each link. Secondly, change of length is derived using Hooke’s Law for each link. Then mapping matrix between change of link length and change of platform position and orientation is derived based on both Euler angle and revolving angle around a spatial axis. Finally, analytical expression of position and orientation errors of the moving platform is derived. Figures of distribution of position and orientation errors in workspace under two velocities are obtained respectively. The results show that, in frequently used workspace, all of the three components of position error are less than 3.5μm. All of them increase with z coordinate of platform center. Position error is influenced slightly by velocity. The difference of position error between two velocities is less than 2%.

Tracking permanent magnets represents a low-footprint and passive approach to monitoring objects or human motion by attaching or embedding magnets therein. Recent tracking techniques achieved high-bandwidth detection considering a simplified model for the magnetic sources, i.e., the dipole model. Nonetheless, such a model can lead to inaccurate results any time a non-spherical magnet approaches the sensor array. Here, we present a novel tracking algorithm based on an analytical model for permanent magnet cylinders with uniform arbitrary magnetization. By means of a physical system mounting 20 magnetometers, we compared the tracking accuracy obtained with our algorithm vs. results obtained by using the dipole model and with respect to a ground-truth reference. With a single magnetic target, our algorithm can significantly lower position (up to 0.68 mm) and orientation errors (up to 2.5°) while enabling online tracking (computation time below 19 ms). We also accurately tracked two magnets, by obtaining a reduction in position error (up to 0.92 mm) vs. the dipole-based algorithm. These findings broaden the applicability of accurate magnetic tracking to real-time applications, facilitating the tracking of multiple magnetic targets in proximity of the magnetic sensors. This advancement opens avenues for applications in wearable devices, advancing the field of motion detection beyond traditional inertial measurement units.

Accuracy test of five-axis CNC machine tool with 3D probe-ball. Part II: errors estimation

The reliable localization for capsule endoscopes is an open research topic. In this study, a low-frequency magnetic localization method for capsule endoscopes with an integrated active coil is proposed. The spatial constraint, the limited battery capacity and the ferromagnetic battery shell of commercial capsules were considered. The generated magnetic flux density was evaluated depending on the distance to the coil and the maximal detectable range was determined. Twelve sensors were arranged in rings and by comparing the measured magnetic flux density with the analytic dipole model, the position and orientation of the coil were reconstructed. The results revealed that the ferromagnetic shell increases the magnetic moment of the coil by approximately a factor of 2.4. Moreover, the mean position and orientation errors were 0.5 mm and 0.3°. Furthermore, by using only the three closest sensors to the coil, a similar localization performance was achieved. Therefore, it was concluded that it is a feasible approach to choose the sensors, which measure the strongest signal to address the problem of the maximal detectable range of magnetic sensors. Moreover, by considering the limited battery capacity, the localization with the proposed coil must be conducted in short time intervals instead of continuously.

Wireless capsule endoscope (WCE) offers a noninvasive investigation of the entire small intestine, which other conventional wired endoscopic instruments can barely reach. As a critical component of the capsule endoscopic examination, physicians need to keep track of the 3D trajectory that the capsule has traveled inside the lower abdomen to identify the positions of the intestinal abnormalities after they are found by the video source. However, existing commercially available radio frequency (RF)-based localization systems can only provide inaccurate and discontinuous position estimation of the WCE due to nonhomogeneity of body tissues and highly complicated distribution of the intestinal tube. In this paper, we present a hybrid localization technique, which takes advantage of data fusion of multiple sensors inside the WCE, to enhance the positioning accuracy and construct the 3-D trajectory of the WCE. The proposed hybrid technique extracts motion information of the WCE from the image sequences captured by the capsule's embedded visual sensor and combines it with the RF signal emitted by the wireless capsule, to simultaneously localize the WCE and mapping the path traveled by the WCE. Experimental results show that the proposed hybrid algorithm is able to reduce the average localization error from 6.8 cm to <;2.3 cm of the existing RF localization systems and a 3-D map can be precisely constructed to represent the position of the WCE inside small intestine.

In order to achieve high precision localization, this paper presents an integrated localization scheme employs two particle filters (PFs) for fusing the inertial navigation systems (INS)-based and the light detection and ranging (LiDAR)-based data. A novel data fusion model is designed, which considers the robot position error, velocity error, and the orientation error. Meanwhile, two-PFs based data fusion filer is designed. The position errors measured by the two-PFs in real tests is 0.059 m. The experimental results verify the effectiveness of two-PFs method proposed in reducing the mobile robot’s position error compared with the two-EKF method.

Geometric errors are the main factors affecting the output accuracy of the parallel spindle head, and it is necessary to perform a sensitivity analysis to extract the critical geometric errors. The traditional sensitivity analysis method analyzes the output position and orientation errors independently, defining multiple sensitivity indices and making it difficult to determine critical geometric errors. In this paper, we propose sensitivity indices that can comprehensively consider position and orientation errors. First, the configuration of the hybrid machine tool is introduced, and the TCP position error model is derived. Then, the tool radius and the effective cutting length are introduced, and the sensitivity indices are defined. After that, the sensitivity analysis of the 3-DOF parallel spindle head is performed using the proposed sensitivity indices, and six critical geometric errors are extracted. The machining accuracy of the parallel spindle head can be greatly improved by improving the critical geometric errors. The proposed sensitivity analysis method can provide important guidance for machine tool accuracy design.

The object of research is a mathematical model describing the movement of a robot with five degrees of freedom for a warehouse. The work was aimed at analyzing the kinematic structure of the manipulator, on the basis of which the base and local coordinate systems were selected, as well as further formalized recording of the kinematic equations in matrix form. It is noted that one of the most problematic places is that the algorithms for controlling the robot most often contain local rules for the interaction of robots between themselves and the external environment, and emergent behavior is manifested as a result of the application of these rules, which does not have a formal description. Therefore, it is important to modernize the models describing the motion of a robot with five degrees of freedom for a warehouse. Using the matrix method, the sequence of constructing coordinate systems is described and its mathematical description is given, which will make it possible to eliminate this drawback in the future. The computer implementation of the developed algorithms was carried out using methods for processing matrix data structures. The principle of constructing a kinematic model of a robot is presented, with the help of which the main coordinate transformation matrices are obtained for robot with five degrees of freedom, and the possibility of taking into account the size of the gaps in the joints is shown. The resulting model is obtained, which is proposed for use in building control algorithms for a robot with an automatic gap selection, as well as in robot calibration. This is due to the fact that the proposed model has a number of features, in particular, the basic coordinate system and the coordinate system of each link of robot with five degrees of freedom are taken into account. This makes it possible to obtain the values of the indicators for the projection of the robot position vector in the initial state, in the rotation of the fourth link at a well-defined angle and in the case of a vertically straightened manipulator. Compared to similar known studies, this provides advantages such as minimizing errors in position, speed and motion accuracy. The object of research is a mathematical model describing the movement of a robot with five degrees of freedom for a warehouse. The work was aimed at analyzing the kinematic structure of the manipulator, on the basis of which the base and local coordinate systems were selected, as well as further formalized recording of the kinematic equations in matrix form. It is noted that one of the most problematic places is that the algorithms for controlling the robot most often contain local rules for the interaction of robots between themselves and the external environment, and emergent behavior is manifested as a result of the application of these rules, which does not have a formal description. Therefore, it is important to modernize the models describing the motion of a robot with five degrees of freedom for a warehouse. Using the matrix method, the sequence of constructing coordinate systems is described and its mathematical description is given, which will make it possible to eliminate this drawback in the future. The computer implementation of the developed algorithms was carried out using methods for processing matrix data structures. The principle of constructing a kinematic model of a robot is presented, with the help of which the main coordinate transformation matrices are obtained for robot with five degrees of freedom, and the possibility of taking into account the size of the gaps in the joints is shown. The resulting model is obtained, which is proposed for use in building control algorithms for a robot with an automatic gap selection, as well as in robot calibration. This is due to the fact that the proposed model has a number of features, in particular, the basic coordinate system and the coordinate system of each link of robot with five degrees of freedom are taken into account. This makes it possible to obtain the values of the indicators for the projection of the robot position vector in the initial state, in the rotation of the fourth link at a well-defined angle and in the case of a vertically straightened manipulator. Compared to similar known studies, this provides advantages such as minimizing errors in position, speed and motion accuracy.

ABSTRACTIn this paper, a robust adaptive controller for a underactuated ship is proposed to make the ship follow a predefined path with guaranteed transient performance and arbitrarily small steady-state position error and orientation error, despite the presence of environmental disturbances induced by wave, wind and ocean current and unknown system parameters. We design a new adaptive state feedback controller and parameter estimators to guarantee converging exponentially by assuming all states are available. It is shown that the mean-square tracking errors are of order of an arbitrarily small design parameter, and the position error and the orientation error also decrease at a pre-specified exponential rate. Simulations with a commercial monohull ship using Matlab also demonstrate the effectiveness of the controllers.

Femur shape prediction by multiple regression based on quadric surface fitting

With the increasing commercial prospect of personal Unmanned Aerial Vehicle (UAV), human and UAV interaction has been a compelling and challenging task. In this paper, we present the RFHUI, a human and UAV interaction system based on passive radio-frequency identification (RFID) technology which provides a remote control function. Three or more Ultra high frequency (UHF) RFID tags are attached on a board to create a hand-held controller. A COTS (Commercial Off-The-Shelf) RFID reader with multiple antennas is deployed to collect the observations of the tags. According to the phase measurement from the RFID reader, we leverage a Bayesian filter based method to localize the position of all tags in a global coordinate. From the estimated position of the attached tags, a 6 DOF (Degrees of Freedom) pose of the controller can be obtained. Therefore, when the user moves the controller, its pose will be precisely tracked in a real-time manner. Then, the flying commands, which are generated from the estimated pose of the controller, are sent to the UAV for navigation. We implemented a prototype of the RFHUI, and the experiment results show that it provides precise poses with 0.045 m error in position and 2.5° error in orientation for the controller. It therefore enables the controller to precisely and intuitively instruct the UAV's navigation in an indoor environment.

Capsule Endoscopy, as a new technology involving integrated circuits, MEMS, image processing, radio transmission, and power supply, makes a significant break-through in the GI examination and therapy. However, there are still many problems for the applications of capsule endoscopes, especially for control or actuation of the capsule movement. Therefore, we propose a new technique to address these problems. First, we enclose a permanent magnet in the capsule, to find its localization and orientation by detecting the magnetic field distribution produced by the magnet, and this magnetic field can be measured by magnetic sensors. Second, we place 3 pairs of Helmholtz coils in spatial orthodox way around the human body, to form a rotative magnetic field, to actuate the magnet, so the capsule is propelled. In our system, the permanent magnet plays a role of both the localization, and actuation. This system is in closed-loop mode by using the feedback message from the localization system. Compared with other MEMS solutions, our actuation system has many advantages: no power supply, small space occupation, high-accuracy for positioning, and it will provide the medical doctor a feasible way to control capsule movement wirelessly.

Video Capsule Endoscope (VCE) sends images of abnormalities in the gastrointestinal (GI) tract. While the physicians receive these images, they have little idea of their exact location which is needed for proper treatment. The proposed localization system consists of a 3D antenna array (with 8 receiver sensors) and one transmitter embedded inside the electronic capsule. We propose an adaptive linearized method of localization using Weighted Centroid Localization (WCL) where the position is calculated by averaging the weighted sum of the reference positions. In our proposed system, first we identify the path loss attenuation exponents using linear least square regression of the collected data (RSSI versus distance). Then the path loss model is linearized to minimize the path loss deviation which is mainly caused due to the nonhomogeneous environment of radio propagation. Then the instantaneous path loss (PL) measured by the sensors is attenuated to the above linearized model and considered as the weight of the sensors to find the location of the capsule using WCL. Finally a calibration process is applied using linear least square regression. To assess the performance, we model the path loss and implement the algorithm in Matlab for 2,530 possible positions with a resolution of 1 mm. The results show that the algorithm achieves high localization accuracy compared with other related methods when simulated using a 3D small intestine model.

In this paper, we propose a mobile robot localization system using appearance based place recognition. Our system uses appearance based place recognition and dead reckoning with Gyrodometry model. We use the theory of the observation likelihood estimation introduced from Fast Appearance Based Mapping (FAB-MAP) for appearance based place recognition. Images collected by a robot produce Bag-of-Words representation and Chow Liu trees. This representation is based on quantized SURF detectors/descriptors. A certain place can be recognized when the image collected matches a reference image coming from the same place in scene database. In addition, problems of appearance based place recognition techniques are solved by using sensor fusion. Experimental results are presented in an outdoor environment. The proposed localization system can achieve the average robot's position error within 2% without GPS in an outdoor environment.