• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 1997.04a
• /
• pp.51-55
• /
• 1997

This study is devote to developing navigation filter for detecting sensor failure in multi-sensor navigation system. In multi-sensor navigation system, Kalman filter is generally used to fuse data of each sensors. Sensor failure is fatal in case that the sensor is used as external measurement of Kalman filter therefore detection and recovery of sensor failure is one the important feature of navigation filter. Generally each sensors have its specific feature in measuring navigational information. Fuzzy theory is proposed to detect external sensor failure and provide valid external measurement to Kalman filter avoiding filter divergence and instability. This idea is applied to Autonomous Underwater Vehicle(AUV) which has two navigation sensor i. e self contained inertial sensor and acoustic external sensor. 2 dimensional simulation result shows acceptable failure detection and recovery

• Journal of Korean Society for Quality Management
• /
• v.49 no.1
• /
• pp.1-15
• /
• 2021

Purpose: The purpose of this study was to propose a sensor fusion algorithm that integrates vehicle motion sensor(VMS) into the hybrid navigation system. Methods: How to evaluate the navigation performance was comparison test with the hybrid navigation system and the sensor fusion method. Results: The results of this study are as follows. It was found that the effects of the sensor fusion method and α value estimation were significant. Applying these greatly improves the navigation performance. Conclusion: For improving the reliability of navigation system, the sensor fusion method shows that the proposed method improves the navigation performance in a combat vehicle.

• Journal of the Korean Society for Precision Engineering
• /
• v.19 no.8
• /
• pp.147-154
• /
• 2002

In this paper, a path navigation algorithm through use of a sensor platform is proposed. The sensor platform is composed of two electric motors which make panning and tilting motions. An algorithm for computing a real path and an obstacle length is developed by using a scanning method that controls rotation of the sensors on the platform. An Autonomous Robot Vehicle(ARV) can perceive the given path by adapting this algorithm. A sensor scanning method is applied to the sensor platform for using small numbers of sensor. The path navigation algorithm is composed of two parts. One is to perceive a path pattern, the other is used to avoid an obstacle. An optimal controller is designed for tracking the reference path which is generated by perceiving the path pattern. The ARV is operated using the optimal controller and the path navigation algorithm. Based on the results of actual experiments, this algorithm for an ARV proved sufficient for path navigation by small number of sensors and for a low cost controller by using the sensor platform with a scanning method.

• Journal of Institute of Control, Robotics and Systems
• /
• v.12 no.10
• /
• pp.982-988
• /
• 2006

The errors of INS (Inertial Navigation System) are known to grow in time. To compensate the accumulated errors, measurements of external or onboard sensors are extensively utilized to form an integrated navigation system. Recently, INS/GPS integrated navigation systems have become popular since exact position and velocity information can be utilized by low cost GPS receivers. Unfortunately, this configuration cannot be trusted at all times especially when there are intentional or unexpected jammings and interruptions. To aid INS irrespectively of these cases, an INS/Image sensor integrated navigation system configuration is designed only based on the information of image sensor gimble angles. The performance of the INS/Image sensor integrated navigation system is evaluated by Monte Carlo simulation.

• Journal of Institute of Control, Robotics and Systems
• /
• v.19 no.2
• /
• pp.102-106
• /
• 2013

A cooperative navigation method for cooperative flight of UAVs is proposed. The commonly used navigation method for UAVs is based on GNSS measurements. However, when it is not available by jamming or other causes, an alternative method is needed. In this paper, it is shown that UAVs equipped with inertial sensors, passive sensor and wireless communication link can perform accurate navigation through sharing information with each other. Firstly, the appropriate roles for sensors and wireless communication link are assigned. Secondly, a filter to perform navigation cooperative is constructed. Finally, the boundedness of estimation error of the filter under small initial estimation error is analyzed. The simulation results show that the proposed method can reduce navigation errors effectively.

• Journal of information and communication convergence engineering
• /
• v.8 no.6
• /
• pp.709-715
• /
• 2010

This paper represents a map building and localization system for mobile robot. Map building and navigation is a complex problem because map integrity cannot be sustained by odometry alone due to errors introduced by wheel slippage, distortion and simple linealized odometry equation. For accurate localization, we propose sensor fusion system using encoder sensor and indoor GPS module as relative sensor and absolute sensor, respectively. To build a map, we developed a sensor based navigation algorithm and grid based map building algorithm based on Embedded Linux O.S. A wall following decision engine like an expert system was proposed for map building navigation. We proved this system's validity through field test.

• Journal of Sensor Science and Technology
• /
• v.19 no.3
• /
• pp.246-257
• /
• 2010

Autonomous guided robot navigation which consists of following unknown paths and avoiding unknown obstacles has been a fundamental technique for unmanned robots in outdoor environments. The unknown path following requires techniques such as path recognition, path planning, and robot pose estimation. In this paper, we propose a novel sensor fusion system for autonomous guided robot navigation in outdoor environments. The proposed system consists of three monocular cameras and an array of nine infrared range sensors. The two cameras equipped on the robot's right and left sides are used to recognize unknown paths and estimate relative robot pose on these paths through bayesian sensor fusion method, and the other camera equipped at the front of the robot is used to recognize abrupt curves and unknown obstacles. The infrared range sensor array is used to improve the robustness of obstacle avoidance. The forward camera and the infrared range sensor array are fused through rule-based method for obstacle avoidance. Experiments in outdoor environments show the mobile robot with the proposed sensor fusion system performed successfully real-time autonomous guided navigation.

• Journal of Institute of Control, Robotics and Systems
• /
• v.8 no.8
• /
• pp.698-705
• /
• 2002

The redundant sensor configuration problem of inertial navigation system(INS) is considered and analyzed the navigation and fault detection performance according to various sensor configurations. We considered various kinds of redundant sensor configurations for symmetric, cone, and orthogonal configurations and compare the navigation and fault detection performance for the configurations. We show that the navigation and fault detection performance is not affected by the coordinate change for a fixed configuration.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.10 no.4
• /
• pp.281-286
• /
• 2010

We propose a space and time based sensor fusion method and a robust landmark detecting algorithm based on sensor fusion for mobile robot navigation. To fully utilize the information from the sensors, first, this paper proposes a new sensor-fusion technique where the data sets for the previous moments are properly transformed and fused into the current data sets to enable an accurate measurement. Exploration of an unknown environment is an important task for the new generation of mobile robots. The mobile robots may navigate by means of a number of monitoring systems such as the sonar-sensing system or the visual-sensing system. The newly proposed, STSF (Space and Time Sensor Fusion) scheme is applied to landmark recognition for mobile robot navigation in an unstructured environment as well as structured environment, and the experimental results demonstrate the performances of the landmark recognition.

• Journal of Institute of Control, Robotics and Systems
• /
• v.10 no.9
• /
• pp.785-798
• /
• 2004

This paper introduces the development of a range sensor based integrated navigation system for a multi-functional indoor service robot, called PSR (Public Service Robot System). The proposed navigation system includes hardware integration for sensors and actuators, the development of crucial navigation algorithms like mapping, localization, and path planning, and planning scheme such as error/fault handling. Major advantages of the proposed system are as follows: 1) A range sensor based generalized navigation system. 2) No need for the modification of environments. 3) Intelligent navigation-related components. 4) Framework supporting the selection of multiple behaviors and error/fault handling schemes. Experimental results are presented in order to show the feasibility of the proposed navigation system. The result of this research has been successfully applied to our three service robots in a variety of task domains including a delivery, a patrol, a guide, and a floor cleaning task.