Chao Hu

A Linear Algorithm for Tracing Magnet Position and Orientation by Using Three-Axis Magnetic Sensors

For medical diagnoses and treatments, it is often desirable to wirelessly trace an object that moves inside the human body. A magnetic tracing technique suggested for such applications uses a small magnet as the excitation source, which does not require the power supply and connection wire. It provides good tracing accuracy and can be easily implemented. As the magnet moves, it establishes around the human body a static magnetic field, whose intensity is related to the magnets 3-D position and 2-D orientation parameters. With magnetic sensors, these magnetic intensities can be detected in some predetermined spatial points, and the position and orientation parameters can be computed. Typically, a nonlinear optimization algorithm is applied to such a problem, but a linear algorithm is preferable for faster, more reliable computation, and lower complexity. In this paper, we propose a linear algorithm to determine the 5-D magnets position and orientation parameters. With the data from five (or more) three-axis magnetic sensors, this algorithm results in a solution by the matrix and algebra computations. We applied this linear algorithm on the real localization system, and the results of simulations and real experiments show that satisfactory tracing accuracy can be achieved by using a sensor array with enough three-axis magnetic sensors.

The Calibration of 3-Axis Magnetic Sensor Array System for Tracking Wireless Capsule Endoscope

A magnetic localization and orientation system is proposed for tracking wireless capsule endoscope. This system uses a small magnet enclosed in the capsule to serve as excitation source. When the capsule moves, the magnet establishes a static magnetic field around. With the magnetic sensor array composed of Honeywell 3-axis magnetic sensors, HMC1053, the magnetic intensities in some pre-determined spatial points can be detected, and the magnets position and orientation parameters can be computed based on an algorithm. To initiate the system and obtain better tracking accuracy, we propose a calibration technique for the magnetic tracking system. The calibration includes sensitivity determination and nonlinearity adjustment, sensor center position and orientation adjustment. Based on the calibration procedures, the system can achieve satisfactory tracking accuracy with the average localization error 3.3 mm and the average orientation error 3.0deg

Efficient magnetic localization and orientation technique for capsule endoscopy

To build a new wireless robotic capsule endoscope with external guidance for controllable and interactive GI tract examination, a sensing system is needed for tracking 3D location and 2D orientation of the capsule movement. An appropriate sensing approach is to enclose a small permanent magnet in the capsule. The magnet establishes a magnetic field around the patients body. With the sensing data of magnetic sensor array outside the patients body, the 3D location and 2D orientation of the capsule can be calculated. Higher localization and orientation accuracy can be obtained if more sensors and proper optimization algorithm are applied. In this paper, different nonlinear optimization algorithms are evaluated, and we have found that Levenberg-Marquardt method provides higher accuracy and faster speed. Simulations were done for investigating the de-noise ability of this algorithm based on different sensor arrays. Furthermore, the real experiment shows that the results are satisfactory with high accuracy.

Efficient face and gesture recognition techniques for robot control

This paper presents a visual recognition system for interactively controlling a mobile robot. First, the robot identifies the operator by human facial recognition, and then determines the actions analyzing the human hand gestures. For facial recognition, the adaptive region-growing algorithm is proposed to estimate the location of face region. A genetic algorithm is then applied to search for the accurate facial feature positions. For gesture recognition, we use adaptive color segmentation, hand finding and labeling with blocking, morphological filtering, and gesture actions are found by template matching, and skeletonizing. The results show 95% correct recognition ratio compared to less than 90% mentioned in other papers.

Robot Rotation Decomposition Using Quaternions

To decompose the three-dimension robot rotation into two sub-rotations, the rotation of the robots main axis and the rotation around this axis, we present a rotation decomposition method by quaternions. By the rotation matrix, we can use the quaternion computation to find the rotation angle of the robot main axis along the axis that is perpendicular to the robot main axis, and the rotation that turns along the robot main axis. In addition, we prove that the decomposition order of the two rotations will not affect the results of the rotation decomposition, and give the procedure for the decomposition. This method has been used to determine the orientation of the wireless capsule endoscope, whose rotation is determined by applying computer vision technique on the captured images

A modular structure for Intemet mobile robots

In this paper we introduce a software and hardware structure for on-line mobile robotic systems. The system hardware configuration mainly consists of a commercially available Pioneer 2 PeopleBot mobile robot, a Sony PTZ video camera and a pair of BreezeNet indoor wireless Ethernet adaptors. The system employs a client-server software architecture in which the client server is insulated from the lower-level details of the mobile robot. This architecture is implemented on the real Internet and the preliminary result is promising. By adopting this modular structure, it will be very easy to construct an experimental platform for the research on diverse teleoperation topics such as remote control algorithms, interface designs, network protocols and applications etc.

Internet-based remote control by using Adaline neural networks

In this paper, we present a remote control scheme for Internet-based teleoperation. This control scheme relies on the real-time estimation of concurrent roundtrip delays in order to optimally assign tasks between the user and the robot. For this purpose, we employ an adaptive linear (Adaline) neural network for which most conventional learning algorithms are infeasible since the computation is usually too intensive to be practical. To get around this problem, we introduce a novel learning algorithm that is based on the maximum entropy principle. Compared to traditional learning algorithms, the computing cost of this algorithm is very low, which makes it possible for the proposed neural network to be implemented on-line in real-time.

Optimal digital control system design for winding shaping process of automobile belt

To maintain uniform string tension and arrangement during the winding shaping process of automobile belt, a digital control system is proposed. The tension is measured by a transducer and regulated by a magnetic powder brake, while the velocity of the shaping model shaft is measured by an opto-coder and driven by a DC motor. In this paper, we present H/sub 2/-optimal control. First, system is derived as a 5-order, 2-input and 2-output state space model. Then the system is discretized, and H/sub 2/-optimal control is realized by following steps: constructing standard sampled-data system; constructing all stabilizing controller; H/sub 2/-optimal control with desired step tracking.

Emerging Maskless Nanolithography Based on Novel Diffraction Gratings

Guanxiao Cheng1,2,3, Yong Yang4, Chao Hu2,3,5, Ping Xu1, Helun Song6, Tingwen Xing4 and Max Q.-H. Meng2,3 1College of Electronic Science and Technology, Shenzhen University, Shenzhen, 2Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 3The Chinese University of Hong Kong, Hong Kong, 4Institute of Optics and Electronics, Chinese Academy of Sciences, Chengdu, 5Ningbo Institute of Technology, Zhejiang University, Ningbo, 6Suzhou Institute of Nano-tech and Nano-bionics, Chinese Academy of Sciences, Suzhou, China