Browsing by Author "Song, KT"

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Agent-based robot control design for multi-robot cooperation
(2005)
Lin, CH
;
Song, KT
;
Anderson, GT
;
電控工程研究所
;
Institute of Electrical and Control Engineering
This paper presents an agent-based robot control (ARC) architecture. ARC-features a flexible realtime control system, which is suitable for multi-robot cooperative tasks. It also provides an efficient platform for building up a multi-robot system consisting of heterogeneous robots. In this paper, an experimental study of this architecture is investigated A cooperative exploration using two mobile robots will be demonstrated. In this experiment, one robot explores the environment by looking for a color-coded target and the other is responsible for task execution at the target position. While exploring in an unknown environment, the first robot, which is equipped with ultrasonic sensors for exploration, records its position as it sees deployed checkpoints. In a later phase, the second robot plans a path to the target directly using information passed from the first robot and get to the target position in an efficient way.
Application of Heuristic Asymmetric Mapping for mobile robot navigation using ultrasonic sensors
(1996-11-01)
Song, KT
;
Chen, CC
;
交大名義發表
;
電控工程研究所
;
National Chiao Tung University
In this paper, an experimental study of a navigation system that allows a mobile robot to travel in an environment about which it has no prior knowledge is described. Data from multiple ultrasonic range sensors are fused into a representation called Heuristic Asymmetric Mapping to deal with the problem of uncertainties in the raw sensory data caused mainly by the transducer's beam-opening angle and specular reflections. It features a fast data-refresh rate to handle a dynamic environment. Potential-field method is used for on-line path planning based on the constructed grid-type sonar map. The mobile robot can therefore learn to find a safe path according to its self-built sonar map. To solve the problem of local minima in conventional potential field method, a new type of potential function is formulated. This new method is simple and fast in execution using the concept from distance-transform path-finding algorithms. The developed navigation system has been tested on our experimental mobile robot to demonstrate its possible application in practical situations. Several interesting simulation and experimental results are presented.
Application of Heuristic Asymmetric Mapping for mobile robot navigation using ultrasonic sensors
(1996-11-01)
Song, KT
;
Chen, CC
;
電控工程研究所
;
Institute of Electrical and Control Engineering
In this paper, an experimental study of a navigation system that allows a mobile robot to travel in an environment about which it has no prior knowledge is described. Data from multiple ultrasonic range sensors are fused into a representation called Heuristic Asymmetric Mapping to deal with the problem of uncertainties in the raw sensory data caused mainly by the transducer's beam-opening angle and specular reflections. It features a fast data-refresh rate to handle a dynamic environment. Potential-field method is used for on-line path planning based on the constructed grid-type sonar map. The mobile robot can therefore learn to find a safe path according to its self-built sonar map. To solve the problem of local minima in conventional potential field method, a new type of potential function is formulated. This new method is simple and fast in execution using the concept from distance-transform path-finding algorithms. The developed navigation system has been tested on our experimental mobile robot to demonstrate its possible application in practical situations. Several interesting simulation and experimental results are presented.
Automatic contour initialization for image tracking of multi-lane vehicles and motorcycles.
(2003)
Tai, JC
;
Song, KT
;
電控工程研究所
;
Institute of Electrical and Control Engineering
This paper presents a novel design for automatic contour initialization and its applications to vision-based traffic monitoring., Active contour models are constructed subsequently to locate And track various types of vehicles, including cars and motorcycles. We propose, to use image measurement to. predict the position and size of vehicles in 6 special designed detection window. The initialization mechanism facilitates contour tracking of different size I vehicle simultaneously At a junction. Actual CCD. images of an artery Junction were employed to verify the proposed image tracking system. Traffic parameters such as, vehicle speed and numbers of vehicles. are obtained With satisfactory accuracy.
Complete coverage motion control of a cleaning robot using infrared sensors
(2005)
Chen, CH
;
Song, KT
;
電控工程研究所
;
Institute of Electrical and Control Engineering
This paper presents a design and implementation of a motion control system for a cleaning robot based on infrared sensors. An infrared sensor system has been developed for complete coverage navigation of a floor-cleaning robot. As the robot adopts a complete coverage cleaning strategy and executes back-and-forth cleaning task, the infrared sensors can help robot align with walls and keep the robot stay in the planned path. Moreover, a landmark has been designed for navigation control using multi-directional infrared signals. Each of them has a unique digital code to facilitate the robot memorize a cleaned area. Thus the robot can complete the cleaning task efficiently in an environment with unexpected static obstacles.
Demosaicing: Heterogeneity-projection hard-decision adaptive interpolation using spectral-spatial correlation
(2006-01-01)
Tsai, CY
;
Song, KT
;
電控工程研究所
;
Institute of Electrical and Control Engineering
A novel heterogeneity-projection hard-decision adaptive interpolation (HPHD-AI) algorithm is proposed in this paper for color reproduction from Bayer mosaic images. The proposed algorithm aims to estimate the optimal interpolation direction and perform hard-decision interpolation, in which the decision is made before interpolation. To do so, a new heterogeneity-projection scheme based on spectral-spatial correlation is proposed to decide the best interpolation direction from the original mosaic image directly. Exploiting the proposed heterogeneity-projection scheme, a hard-decision rule can be designed easily to perform the interpolation. We have compared this technique with three recently proposed demosaicing techniques: Lu's, Gunturk's and Li's methods, by utilizing twenty-five natural images from Kodak PhotoCD. The experimental results show that HPHD-AI outperforms all of them in both PSNR values and S-CIELab Delta E-ab* measures.
Demosaicing: Heterogeneity-projection hard-decision adaptive interpolation using spectral-spatial correlation - art. no. 606906
(2006)
Tsai, CY
;
Song, KT
;
電控工程研究所
;
Institute of Electrical and Control Engineering
A novel heterogeneity-projection hard-decision adaptive interpolation (HPHD-AI) algorithm is proposed in this paper for color reproduction from Bayer mosaic images. The proposed algorithm aims to estimate the optimal interpolation direction and perform hard-decision interpolation, in which the decision is made before interpolation. To do so, a new heterogeneity-projection scheme based on spectral-spatial correlation is proposed to decide the best interpolation direction from the original mosaic image directly. Exploiting the proposed heterogeneity-projection scheme, a hard-decision rule can be designed easily to perform the interpolation. We have compared this technique with three recently proposed demosaicing techniques: Lu's, Gunturk's and Li's methods, by utilizing twenty-five natural images from Kodak PhotoCD. The experimental results show that HPHD-AI outperforms all of them in both PSNR values and S-CIELab Delta E-ab* measures.
Design and experimental study of an ultrasonic sensor system for lateral collision avoidance at low speeds
(2004)
Song, KT
;
Chen, CH
;
Huang, CHC
;
電控工程研究所
;
Institute of Electrical and Control Engineering
In this study, we design and implement an ultrasonic sensor system for lateral collision avoidance of vehicles at low speeds. The developed sensor system is useful for detecting vehicles, motorcycles, bicycles and pedestrians that pass by the lateral side of a vehicle. The system can be adopted to enhance the rear-view mirrors of present vehicles, which have blind spots on the lateral sides. Ultrasonic sensors, which have been widely used on cars for rear object detection during parking, are developed for lateral object detection at low speeds. Detailed experimental studies are presented in this paper. Experimental results show that the proposed system can detect a vehicle at speeds up to 40km/hr with a maximum range of 6 meters. Moreover, the influence of wind on:the measurement is also investigated The developed sensor system gives satisfactory results for a wind speed up to 35km/hr.
Dynamic motion planning based on real-time obstacle prediction
(1996)
Chang, CC
;
Song, KT
;
電控工程研究所
;
Institute of Electrical and Control Engineering
Embedded CMOS imaging system for real-time robotic vision
(2005)
Andrian, H
;
Song, KT
;
電控工程研究所
;
Institute of Electrical and Control Engineering
This paper presents a real-time robotic vision system that provides visual information for a control scheme of mobile manipulation. The hardware implementation consists of a CMOS image board and a TI DSP board which uses C6416 as the main processor. The merits of using these two boards are the construction of a low cost embedded platform with high performance. Meanwhile the software implementation proposes a visual servoing using a behavior-based approach to solving the mobile manipulator control problem. The description of the hardware and software implementation is given and experimental results are discussed.
Environment perception for a mobile robot using double ultrasonic sensors and a CCD camera
(1996-06-01)
Song, KT
;
Tang, WH
;
電控工程研究所
;
Institute of Electrical and Control Engineering
To move efficiently in an unknown or uncertain environment, a mobile robot must use observations taken by various sensors to construct information for path planning and execution, A reasonably accurate representation of the external world would also be very useful for robot self-localization. One of the merits of applying multiple sensors to a mobile robot is the enhancement of environment recognition. In this paper, we propose to use sensory information combined from double ultrasonic sensors and a CCD camera. We developed an algorithm based on a dual-transducer design to eliminate errors resulting from the beam opening angle of ultrasonic sensors. An extended discrete Kalman filter (EDKF) was designed to fuse raw sensory data and to reduce the influence of specular reflection of ultrasonic type transducers, thereby providing a more reliable representation for enviroment perception. Computer simulation as well as practical experimental results demonstrate that this sensory system can provide useful and comprehensiv,.e environment perception for intelligent robotics.
Environment perception for a mobile robot using double ultrasonic sensors and a CCD camera
(1996-06-01)
Song, KT
;
Tang, WH
;
交大名義發表
;
電控工程研究所
;
National Chiao Tung University
To move efficiently in an unknown or uncertain environment, a mobile robot must use observations taken by various sensors to construct information for path planning and execution, A reasonably accurate representation of the external world would also be very useful for robot self-localization. One of the merits of applying multiple sensors to a mobile robot is the enhancement of environment recognition. In this paper, we propose to use sensory information combined from double ultrasonic sensors and a CCD camera. We developed an algorithm based on a dual-transducer design to eliminate errors resulting from the beam opening angle of ultrasonic sensors. An extended discrete Kalman filter (EDKF) was designed to fuse raw sensory data and to reduce the influence of specular reflection of ultrasonic type transducers, thereby providing a more reliable representation for enviroment perception. Computer simulation as well as practical experimental results demonstrate that this sensory system can provide useful and comprehensiv,.e environment perception for intelligent robotics.
Environment prediction for a mobile robot in a dynamic environment
(1997-12-01)
Chang, CC
;
Song, KT
;
電控工程研究所
;
Institute of Electrical and Control Engineering
The problem of navigating a mobile robot among moving obstacles is usually solved on the condition of knowing the velocity of obstacles. However, it is difficult to provide such information to a robot in real time. In this paper, we present an environment predictor that provides an estimate of future environment configuration by fusing multisensor data in real time. The predictor is implemented by an artificial neural network (ANN) trained using a relative-error-backpropagation (REBP) algorithm. The REBP algorithm enables the ANN to provide output data with a minimum relative error, which is better than conventional backpropagation (BP) algorithms in this prediction application. The mobile robot can, therefore, respond to anticipated changes in the environment. The performance is verified by prediction simulation and navigation experiments.
Environment prediction for a mobile robot in a dynamic environment
(1997-12-01)
Chang, CC
;
Song, KT
;
電控工程研究所
;
Institute of Electrical and Control Engineering
The problem of navigating a mobile robot among moving obstacles is usually solved on the condition of knowing the velocity of obstacles. However, it is difficult to provide such information to a robot in real time. In this paper, we present an environment predictor that provides an estimate of future environment configuration by fusing multisensor data in real time. The predictor is implemented by an artificial neural network (ANN) trained using a relative-error-backpropagation (REBP) algorithm. The REBP algorithm enables the ANN to provide output data with a minimum relative error, which is better than conventional backpropagation (BP) algorithms in this prediction application. The mobile robot can, therefore, respond to anticipated changes in the environment. The performance is verified by prediction simulation and navigation experiments.
Experimental study on robot visual tracking using a neural controller
(1996)
Song, KT
;
Chang, JM
;
交大名義發表
;
電控工程研究所
;
National Chiao Tung University
Visual tracking of a moving object has been an active research topic in the field of robotics and computer vision. In this paper, an experimental study is presented on a neural control design of a robotic manipulator to track a moving object using visual information. The proposed system integrates CCD visual data into an artificial neural network (ANN) for robot arm motion control. This design strategy features fast and efficient control approach where the computation load is reduced to fit the real-time requirement. Integrated experiments have been carried out using a Mitubishi RV-M2 industrial robot equipped with a CCD camera. After training the ANN controller with experimental data, the transformation from world coordinate to the robot coordinate can be eliminated. Robot motion control can be achieved without solving inverse kinematics of the manipulator. Furthermore, the proposed visual tracking system dose not require calibration data of the camera. The factors affecting tracking performance is analyzed and discussed.
Face recognition and tracking for human-robot interaction
(2004)
Song, KT
;
Chen, WJ
;
電控工程研究所
;
Institute of Electrical and Control Engineering
This paper presents a design and experimental study of human-robot interaction via face recognition and image tracking. A new architecture is proposed for fast face recognition of family members. In the proposed system, each family member has his/her own RBF neural networks. Each neural network is only responsible for recognizing its trained member. Consequently, the database is small and the processing time required for face recognition is minimized. A recognition rate of 94% has been achieved, an improvement relative to conventional approaches. In order to detect and track a person, we also developed an algorithm for detecting multiple faces in a scene based on division of skin and hair color regions. The face recognition and image tracking system has been integrated to an experimental mobile robot. Practical experiments reveal that the robot demonstrates real-time face recognition and tracking performance.
Fast optical flow estimation and its application to real-time obstacle avoidance
(2001)
Song, KT
;
Huang, JH
;
電控工程研究所
;
Institute of Electrical and Control Engineering
This paper presents a novel fast optical flow estimation algorithm and its application to real-time obstacle avoidance of a guide-dog robot. The function of the laboratory-developed robot is to help blind or visually impaired pedestrians to move safely among obstacles. The proposed algorithm features a combination of the conventional correlation-based principle and the differential-based method for optical flow estimation. Employing image intensity gradients as features for pattern matching, we set up a brightness constraint to configure the search area. The merit of this scheme is that the computation load can be greatly reduced and in the mean time the possibility of estimation error is decreased. The vision system has been established on board the robot to provide depth information of the immediate environment. The depth data are transformed to a safety distribution histogram and used for real-time obstacle avoidance. Experimental results demonstrate that the proposed method is effective for a guidance robot in a dynamic environment.
Fast parking control of mobile robots: A motion planning approach with experimental validation
(2004-09-01)
Lee, TC
;
Tsai, CY
;
Song, KT
;
電控工程研究所
;
Institute of Electrical and Control Engineering
This paper presents a solution to the general parking problem of nonholonomic mobile robots based on motion planning and tracking controller design. A new global tracking controller is first proposed to achieve global uniformly asymptotic stability and local exponential convergence. The parking problem is then transformed into a tracking one by adding a redesigned virtual trajectory to the original trajectory, thus guaranteeing practical stability with exponential convergence. Further improvement in parking performance is obtained through. linearization and pole-placement methods. One feature of our approach is that fast convergence in parking and tracking can be treated at the same time without switching between two controllers. Moreover, a tuning function is used to enhance parking performance. With the proposed framework, various tracking controllers given in the literature can be adopted to handle parking problems. The effectiveness of the proposed methods is verified by several interesting experiments including parallel parking and back-into-garage parking.
Heuristic fuzzy-neuro network and its application to reactive navigation of a mobile robot
(2000-03-16)
Song, KT
;
Sheen, LH
;
電控工程研究所
;
Institute of Electrical and Control Engineering
A novel pattern recognition approach to reactive navigation of a mobile robot is presented in this paper. A heuristic fuzzy-neuro network is developed for pattern-mapping between quantized ultrasonic sensory data and velocity commands to the robot. The design goal was to enable an autonomous mobile robot to navigate safely and efficiently to a target position in a previously unknown environment. Useful heuristic rules were combined with the fuzzy Kohonen clustering network (FKCN) to build the desired mapping between perception and motion. This method provides much faster response to unexpected events and is less sensitive to sensor misreading than conventional approaches. It allows continuous, fast motion of the mobile robot without any need to stop for obstacles. The effectiveness of the proposed method is demonstrated in a series of practical tests on our experimental mobile robot. (C) 2000 Elsevier Science B.V. All rights reserved.
Image-based turn ratio measurement at road intersection
(2005)
Song, KT
;
Tai, JC
;
電控工程研究所
;
Institute of Electrical and Control Engineering
The measurement of vehicle turn ratio and based on that a prediction of the probability of a car to make a turn at an intersection are useful information for advanced traffic prediction and control. Conventional vision-based vehicle detection procedures that merely count the number of passing vehicles are not sufficient for turn ratio measurement, because they cannot tell where the vehicles come from at an intersection. This paper presents an image-based system for real-time turn ratio measurement. A method is proposed to estimate automatically the turn ratio of an intersection by using the techniques of detection window and optical flow calculation of motion vectors. A stand-alone image measurement system has been installed at a busy road junction in Hsinchu Science Park. Experimental results reveal that the average measurement error is within 2%.