Develop a multi-detection security system using multi-sensor fusion algorithms

The paper develops the multi-detection system using multi-level surveillance structure. The system contains active detection modules, passive detection modules, a supervised computer, an image system and an intelligent home. The passive detection modules contain wire/wireless detection modules and appliance control modules, and decide the event to be true or not using fusion algorithms, and transmit detection signals to the supervised computer via wire/wireless interface. Mobile robots are active detection modules and carry various sensors to search dangerous events. Each mobile robot transmits the real-time event signal to the supervised computer and the other mobile robots via wireless RF interface. The image system detects fire source using Otsu algorithm. The system integrates wire/wireless passive detection modules, mobile robots and image system to detect fire source using weighted average method. If the fire event occurs, the supervised computer calculates the dangerous grade using logical filter method according to the signals of detection modules in the first step, and transmits the position of the fire event to the other mobile robots. The assigned mobile robots move to the event location for double check autonomously, and transmit the detection results to the supervised computer. The supervised computer gives the final decision according to the feedback signals in the second step. Finally, we present some experimental scenarios using passive detection modules, active detection modules and image system for the fire detection in the intelligent home.     

Mobile robot localization by fuzzy logic fusion of multisensor data

Interest has been growing in the use of different sensors to increase the capabilities of navigation systems of autonomous vehicles. This area has been studied by several researchers. Nevertheless, this problem has not been solved in a fully satisfying manner. We proposed the method of global, long-term position estimation in a known environment. The method does not require any a priori position prediction or estimation. It is especially suitable in the case of using very simple sensors. The algorithm is based on fuzzy logic fusion of data received from several sensors for some time period. We discuss the methodology of solution evaluation and present some examples of typical criteria. Results of first computer simulation are presented.     

Minimal representation multisensor fusion using differentialevolution

Fusion of information from multiple sensors is required for planning and control of robotic systems in complex environments. The minimal representation approach is based on an information measure as a universal yardstick for fusion and provides a framework for integrating information from a variety of sources. In this paper, we describe the principles of minimal representation multisensor fusion and evaluate a differential evolution approach to the search for solutions. Experiments in robot manipulation using both tactile and visual sensing demonstrate that this algorithm is effective in finding useful and practical solutions to this problem for real systems. Comparison of this differential evolution algorithm with more traditional genetic algorithms shows distinct advantages in both accuracy and efficiency     

多传感器数据融合系统中的目标跟踪技术

概述了多传感器数据融合系统中目标跟踪的主要技术,分析比较了最近邻法、联合概率法进行数据互联的原理、性能及优缺点,讨论了滤波和Kalman滤波的性能及适用的目标运动模型,并分别给出了用两种互联方法、两种滤波方法进行计算机仿真时的误差比较。实验结果表明,用多传感器数据融合系统进行目标跟踪可以得到较高的跟踪精度。     

多传感器数据融合技术与专家系统研究

简要分析多传感器数据融合技术的理论及研究方法。介绍基于规则的专家系统法在数据融合中的应用;分析专家系统的功能和结构,产生式规则的专家系统的知识表示;介绍正向推理机的设计等。     

Motion estimation of 3-D objects using multisensor data fusion

This article presents an approach to estimate the general 3-D motion of a polyhedral object using multiple sensor data some of which may not provide sufficient information for the estimation of object motion. Motion can be estimated continuously from each sensor through the analysis of the instantaneous state of an object. The instantaneous state of an object is specified by the rotation, which is defined by a rotation axis and rotation angle, and the displacement of the center of rotation. We have introduced a method based on Moore-Penrose pseudoinverse theory to estimate the instantaneous state of an object, and a linear feedback estimation algorithm to approach the motion estimation. The motion estimated from each sensor is fused to provide more accurate and reliable information about the motion of an unknown object. The techniques of multisensor data fusion can be categorized into three methods: averaging, decision, and guiding. We present a fusion algorithm which combines averaging and decision. With the assumption that the motion is smooth, our approach can handle the data sequences from multiple sensors with different sampling times. We can also predict the next immediate object position and its motion. The simulation results show our proposed approach is advantageous in terms of accuracy, speed, and versatility.     

Detection of Asia dust storms using multisensor satellite measurements

Observations from visible, infrared and microwave satellite instruments are integrated to detect dust storm over northwestern China. Microwave measurements are used to detect the dust storm underneath ice clouds, while visible and infrared measurements are utilized for delineating the cloud-free dust systems. Detection is based on microwave polarized brightness temperature differences (ΔT_b = T_bv − T_bh) among two channels of 89 GHz and 23.8 GHz and infrared brightness temperature difference (BTD) between channels at 11 and 12 μm. It is shown that the integrated approach is better than the method solely based on infrared BTD in storm detection, especially for those dust systems covered by ice clouds. This approach is applied for the Asia dust storms cases using the data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Advanced Microwave Scanning Radiometer (AMSR-E) onboard Aqua satellite.     

Cadaver study for spinal fusion surgery using an image-guided surgical robot system

We present a novel surgical robotic system for spinal fusion that includes a computer-based planning algorithm, O-type bi-planar fluoroscopy, and a surgical robot. The planning system determines a surgical path based on fluoroscopy images or a 3D image reconstructed using pre-operative CT data. The robot guides the surgical path that the surgeon generates with the planning system. In this cadaver study, we tested the performance of the robotic system in the treatment of eight lumbar vertebrae by comparing CT images recorded before and after surgery.     

Workspace mapping based on multisensor information fusion using heterogeneous onboard sensors

In recent years, multiple robot systems that perform team operations have been developed. These robot systems are expected to execute complicated tasks smoothly in a given congested workspace. In this article, we propose a workspace mapping algorithm using ultrasonic stereo sonar and an image sensor in order to operate the mobile robots among obstacles. This workspace mapping algorithm involves two steps: (1) the position detection of obstacles using ultrasonic stereo sonar, and (2) the shape detection of obstacles using an image sensor. While each robot moves around in the given workspace, the two steps of the mapping algorithm are repeated and sensor data are collected. The robot measures the distance and the direction of obstacles using ultrasonic stereo sonar. The shape of obstacles is also captured using an onboard image sensor. A workspace map is created based on the sensor data accumulated from the proposed method, and successful results are also obtained through experiments.     

Multisensor based security robot system for intelligent building

Intelligent building can provide safety, convenience, efficiency and entertainment for life in the 21st century. The most importance role of the intelligent building is the security system. We develop a multi sensor-based intelligent security robot (ISR) that is widely employed in intelligent buildings. The intelligent security robot can detect abnormal and dangerous situations and notify users. The robot has the shape of cylinder and its diameter, height, and weight are 50 cm, 130 cm and 100 kg respectively. The function of the ISR contains six parts. There is the software development system; avoiding obstacle and motion planning system, image system, sensor system, remote supervise system and other systems. We develop a multi sensor-based sensor system in the ISR. We use multiple multisensor fusion algorithms to get an exact decision in the detection subsystem of the sensor system. There is an adaptive fusion method, a rule based method, and a statistical signal method. We demonstrate the remote supervisory system to control the ISR using a direct control mode and a behavior control mode. We think that the man–machine interface in a security robot system must have mobility and convenience. Therefore, we use a touch screen to display the system state, and design a general user interface (GUI) to service the user and visitors. The user can remotely control the appliance using a cell phone through a GSM modem, too. The appliance module can feedback reaction results to the user through a cell phone. Finally, we implement the fire detection system in the intelligent security robot (Chung-Cheng-I). If a fire occurs, the intelligent security robot can find out the fire source using the fire detection system. In intruder detection, we program the same scenario to detect the intruder using the intelligent security robot. The intelligent security robot transmits the message of the detection result to the user using a GSM modem for a fire event or intruder, and transmits the detection result to a client computer through the internet.     

多传感器数据融合的一种方法

在多传感器数据融合的过程中,首先必须验证各个传感器的可靠程度,即确立正确的关系矩阵。一般做法是根据门限值判断两个传感器是否相互支持,或者用分段直线等方法表示其支持程度。在分析的基础上,提出了应用椭圆曲线表示支持程度,并分别给出了融合结果。     

Control for a rings gymnastic robot using fuzzy reasoning and genetic algorithms

The rings event is part of men's apparatus gymnastics. The ring exercise have free-floating characteristics of the gripping point. Here, we propose a novel “rings gymnastic robot” aimed at an application in gymnastic coaching. The purpose of this article is to develop fuzzy control rules to realize performances on the rings by considering torque minimization by genetic algorithms (GAs), because these rules should be useful in coaching. The effectiveness of the controllers obtained is illustrated by a simulation. This work was presented, in part, at the Sixth International Symposium on Artificial Life and Robotics, Tokyo, Japan, January 15–17, 2001     

Pipe inspection robot using a wireless communication system

Pipe lines of any material need to be inspected after a certain number of years. Therefore, it is necessary to develop a flexible pipe inspection robot using a wireless communication system. In this research, a wireless communication system is tested, and it is verified that the system can transmit image information steadily at a high speed. On the basis of this wireless communication system, a new pipe inspection robot for drain pipes is developed. With this new system, the movement of the robot can be controlled, defects or other problems inside a pipe can be inspected, and an image of the inside of the pipe can also be transmitted in real time.     

Cartesian path generation of robot manipulators using continuous genetic algorithms

In this paper, the authors describe a novel technique based on continuous genetic algorithms (CGAs) to solve the path generation problem for robot manipulators. We consider the following scenario: given the desired Cartesian path of the end-effector of the manipulator in a free-of-obstacles workspace, off-line smooth geometric paths in the joint space of the manipulator are obtained. The inverse kinematics problem is formulated as an optimization problem based on the concept of the minimization of the accumulative path deviation and is then solved using CGAs where smooth curves are used for representing the required geometric paths in the joint space through out the evolution process. In general, CGA uses smooth operators and avoids sharp jumps in the parameter values. This novel approach possesses several distinct advantages: first, it can be applied to any general serial manipulator with positional degrees of freedom that might not have any derived closed-form solution for its inverse kinematics. Second, to the authors’ knowledge, it is the first singularity-free path generation algorithm that can be applied at the path update rate of the manipulator. Third, extremely high accuracy can be achieved along the generated path almost similar to analytical solutions, if available. Fourth, the proposed approach can be adopted to any general serial manipulator including both nonredundant and redundant systems. Fifth, when applied on parallel computers, the real time implementation is possible due to the implicit parallel nature of genetic algorithms. The generality and efficiency of the proposed algorithm are demonstrated through simulations that include 2R and 3R planar manipulators, PUMA manipulator, and a general 6R serial manipulator.     

Neural network control system of cooperative robot based on genetic algorithms

Neural Computing and Applications - Attitude detection of cooperative robots can help robots recognize environment, understand tasks, and improve the safety, accuracy and efficiency of robot work....     

多传感器数据的统计融合方法

在多传感数据融合过程中 ,各传感器的可靠程度的确定是至关重要的。利用统计方法理论 ,将各传感器的可靠程度模糊化 ,进而给出各传感器的综合支持程度指标 ,并在此指标基础上给出多传感器数据的融合结果。该方法计算简便 ,其结论较为稳定     

Multi-sensor data fusion using NIHS transform and decomposition algorithms

Multi-spectral image fusion is to enhance the details present in multi-spectral bands with the spatial information available in the panchromatic image. Fused images have the effect of spectral distortions and lack of structural similarity. To overcome these limitations, three methods are proposed using intensity, hue, saturation (IHS) and nonlinear IHS (NIHS) transform along with the Dynamic Mode Decomposition (DMD) and 2D-Empirical Mode Decomposition (2D-EMD or IEMD). An intensity plane is calculated from the NIHS transform. The modes are constructed using DMD by considering the variations between the intensity plane computed using NIHS transforms of a low resolution multi-spectral image and a panchromatic image. Similarly, 2D-EMD is also used for image fusion. Modes are subjected to weighted fusion rule to get an intensity plane with spatial and edge information. Finally, the calculated intensity plane is concatenated along with the hue and saturation plane of low-resolution multi-spectral image and transformed into RGB color space. Thus, the fused images have high spatial and edge information on spectral bands. The experiments and its quality assessment assure that proposed methods perform better than the existing methods.