K.L. Su

Multisensor fusion and integration: approaches, applications, and future research directions

Multisensor fusion and integration is a rapidly evolving research area and requires interdisciplinary knowledge in control theory, signal processing, artificial intelligence, probability and statistics, etc. The advantages gained through the use of redundant, complementary, or more timely information in a system can provide more reliable and accurate information. This paper provides an overview of current sensor technologies and describes the paradigm of multisensor fusion and integration as well as fusion techniques at different fusion levels. Applications of multisensor fusion in robotics, biomedical system, equipment monitoring, remote sensing, and transportation system are also discussed. Finally, future research directions of multisensor fusion technology including microsensors, smart sensors, and adaptive fusion techniques are presented.

Automatic docking and recharging system for autonomous security robot

To keep autonomous mobile robot in continuously working condition, power supply is an important issue. Typically, rechargeable batteries may provide few hours of peak usage. Recharging is necessary before the power of the batteries has exhausted. In this paper, the docking station with an auto-recharging device and robot docking mechanism are implemented. We propose a docking control strategy and automatic recharging device for the security robot recharging. We also propose a power prediction algorithm to determine when the robot needs to navigate back to docking station for recharging. An artificial landmark is detected and recognized by the proposed image processing system. Then the geometrical relationship between the robot and the docking station (the depth and orientation) is estimated. The robot will move directly right in front of the docking station. Finally, the robot approaches to the docking station based on the proposed virtual spring model. In this model, we assume that the robot and the docking station are connected by a virtual spring. The compliant forces act both in the direction of the translation deformation and bending. The motion control parameters, which are velocities of the two wheels, can be derived from the model. Experimental results show that the proposed methods successfully perform the docking and automatic recharging.

Fire detection and isolation for intelligent building system using adaptive sensory fusion method

Describes an algorithm and experimental results for detecting and isolating sensory failures for a fire detection system. In the fire system, we use two smoke sensors, two flame sensors and two temperature sensors to detect fire events. These sensors can be classified into two groups, and each group has one smoke sensor one flame sensor and one temperature sensor. The sensory failure and isolation techniques described in the paper are based on weight variation of the sensory adaptive fusion method. From the simulation and experimental implementation results, it demonstrates that the method can exactly find out which sensor is faulty and isolate it. That is to say, when a sensory failure occurs, the system can exactly locate the sensory failure.

A review of high-level multisensor fusion: approaches and applications

The potential advantages in multisensor fusion can be obtained more accurately, concerning feature that are impossible to perceive with individual sensors, as well as in less time, and at a lower cost. The characterization most commonly encountered in the rapidly growing multisensor fusion literature based on levels of detail in the information is that of the now well known triple low level (data level), medium level (feature level) and high level (decision level). The development of high-level multisensor fusion representations is very important, in the construction of advanced intelligent systems. The paper begins with a review on the fundamental principles about high-level multisensor fusion, together with some of the applications. Finally, we compare the decision algorithms in the high-level multisensor fusion.

A multiagent multisensor based real-time sensory control system for intelligent security robot

The security of home, laboratory, office and factory is essential to human daily life. A danger event is often caused by the negligence of humans. Potential hazards may injure our life. Therefore, it motivates us to develop an intelligent multi-sensor based Security Robot system. It is expected to be widely employed in our daily life. Security robot can detect dangerous situation and provide timely alert us. The structure of the security robot contains eight parts. Including remote surveillance and control system, image system, obstacle avoidance system, software system, auto-dialing, driver system, sensor system and motion planning system. In this paper, we discuss the opportunity to use multi-agent technology in the sensory system and the expected improvements. The sensory system has seven-variety detection and diagnosis agent (local agent) and one sensor agent (auxiliary agent). Finally, we use multi-processor architecture to implement the multi-agent based sensory system for the security robot application.

The development of intelligent home security robot

The security system of home and building is an important issue to human daily life. We develop a multiple remote interface security system (MRlSS), that integrated with intelligent security robot (ISR), security supervise computer, GSM module, RF interface and appliances control module. The multiple remote interface security system can detect abnormal and dangerous situation and notify us through Internet, or send the message to cellular phone through GSM module. The MRISS can control the appliance control module using wireless RF interface. The user can remote control appliance using cell phone through GSM module, too. The appliance module can feedback reaction result to the user through cell phone. First, we develop the communication protocol in MRISS, and design the multiple interface security robot, security module and appliance control module. Then we implement the MRISS function using the proposed method applying in security detection and appliance control. We can monitor the condition in home or building through Internet, and receive a message of the detection information to cellular phone using wireless RF interface embedded in the ISR. We can also use cell phone to instruct ISR to control appliances. ISR controls appliances via wireless RF module. We have developed and demonstrated the success of the project presented situation here in.

Multilevel multisensor based decision fusion for intelligent animal robot

The objective of the paper is to develop multilevel multisensor based decision fusion principles for an intelligent animal robot. The paper presents the design and implementation of a four-legged animal robot. The animal robots head, body, and legs were constructed using aluminum material. The control/decision unit, driver unit and sensory unit were designed for the control of the animal robot. In addition, we use hierarchically organized control hardware and multilevel multisensor based fusion techniques to obtain a fused decision. Weight function and rule based algorithms are employed to fuse and integrate multisensor data. Preliminary experimental results indicate that the proposed methods can effectively fuse decisions for the animal robot.

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.

Multisensor Based Security Robot System for Intelligent Building

Intelligent building can provide safety, convenience, efficiency and entertainment for life in the 21 century. The most importance role of the intelligent building is security system. In the paper, we focus on the fire detection and intruder detection of the security system, and use intelligent security robot to guard the safety for life and wealth in the intelligent building. We propose an adaptive fusion method for fire detection, and uses smoke sensor, flame sensor and temperature sensor to detect fire occurred. In reality, the phenomenon of the fire may have smoke, flame and high temperature. Then we use rule based method to detect intruder, and fuse body sensors, ultrasonic sensors and IR sensors to detect intruder. Finally, we implement the fire detection system in the intelligent security robot (Chung-Cheng-I). If fire occurred, the security robot can find out the fire source using the fire detection system. In the intruder detection, we program the same scenario to detect the intruder using the intelligent security robot. The intelligent security robot transmits the message of detection result to the user using GSM modem for fire event and intruder, and transmits the detection result to client computer through Internet

A multiagent multisensor based security system for intelligent building

The security of buildings, homes, laboratories, offices and factories is essential to human life. An unlucky event is often caused by human negligence. We have developed a multiagent multisensor-based security system or intelligent building. The system can be widely employed in daily life and can detect dangerous situations using sensors. The structure of the security system is divided into four parts, the fire detection/diagnosis agent, intruder detection/diagnosis agent, environment detection/diagnosis agent, and power detection/diagnosis agent. In this paper, we use an adaptive data fusion method in the fire detection/diagnosis agent and use a rule-based method in the intruder detection/diagnosis agent. We use statistical signal detection theory in the environment detection/diagnosis agent, and use a fault detection and isolation procedure (FDIP) in the power detection/diagnosis agent. The security system has a four-variety detection/diagnosis agent. Finally, we implement these methods using computer simulation and achieve quite satisfactory results.