• Title/Summary/Keyword: Target-object Recognition

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Path Planning of Autonomous Mobile Robot Based on Fuzzy Logic Control (퍼지로직을 이용한 자율이동로봇의 최적경로계획)

  • Park, Jong-Hun;Lee, Jae-Kwang;Huh, Uk-Youl
    • Proceedings of the KIEE Conference
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    • 2003.07d
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    • pp.2420-2422
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    • 2003
  • In this paper, two Fuzzy Logics for path planning of an autonomous mobile robot are proposed. If a target point is given, such problems regarding the velocity and object recognition are closely related with path to which the mobile robot navigates. Therefore, to ensure safety navigation of the mobile robot for two fuzzy logic parts, path planning considering the surrounding environment was performed in this paper. First, feature points for local and global path are determined by utilizing Cell Decomposition off-line computation. Second, the on-line robot using two Fuzzy Logics navigates around path when it tracks the feature points. We demonstrated optimized path planning only for local path using object recognition fuzzy logic corresponds to domestic situation. Furthermore, when navigating, the robot uses fuzzy logic for velocity and target angle. The proposed algorithms for path planning has been implemented and tested with pioneer-dxe mobile robot.

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Synthetic hit-miss transform for optical recognition of a moving target (이동물체의 광학적 인식을 위한 합성 HMT)

  • 김종찬;김정우;이하운;도양회;김수중
    • Journal of the Korean Institute of Telematics and Electronics D
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    • v.35D no.3
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    • pp.82-90
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    • 1998
  • A hit-miss transform(HMT) using synthetic structuring elements(SE's) for optical recognition of a moving target is proposed. A moving target which was obtained from a fixed view point has objects. In proposed HMT, SE's are synthesized by using SDF(synthetic discriminant function) algorithm for efficient recognitionof various shapes of true class objects in noisy and cluttered scene. The synthetic hit SE and the synthetic miss SE are composed of SDF of hit SE's and miss SE's for each true class object. Simulation results show the proposed method can be used for the recognition of various shapes of the true class with one one HMT operation.

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A Study on target tracking system for a mobile robot using ultrasonic sensors

  • Kim, Hon-Hui;Han, Dong-Hui;Ha, Yun-Su
    • 제어로봇시스템학회:학술대회논문집
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    • 2001.10a
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    • pp.134.5-134
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    • 2001
  • The capability of environment recognition is very important for mobile robot. Especially, a function of target tracking is necessary in monitoring and watching an object using mobile robot. In general, vision sensors such as CCD camera and laser range finder were used for tracking of a moving target. However, they are not only affected by intensity of illumination in environment but also require high performance processors to process large amount of data. Therefore, in this paper, we propose the construction of target tracking system for mobile robot using only ultrasonic sensors to cope with these problems.

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Strategy of Object Search for Distributed Autonomous Robotic Systems

  • Kim Ho-Duck;Yoon Han-Ul;Sim Kwee-Bo
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.6 no.3
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    • pp.264-269
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    • 2006
  • This paper presents the strategy for searching a hidden object in an unknown area for using by multiple distributed autonomous robotic systems (DARS). To search the target in Markovian space, DARS should recognize th ε ir surrounding at where they are located and generate some rules to act upon by themselves. First of all, DARS obtain 6-distances from itself to environment by infrared sensor which are hexagonally allocated around itself. Second, it calculates 6-areas with those distances then take an action, i.e., turn and move toward where the widest space will be guaranteed. After the action is taken, the value of Q will be updated by relative formula at the state. We set up an experimental environment with five small mobile robots, obstacles, and a target object, and tried to research for a target object while navigating in a un known hallway where some obstacles were placed. In the end of this paper, we present the results of three algorithms - a random search, an area-based action making process to determine the next action of the robot and hexagon-based Q-learning to enhance the area-based action making process.

HandButton: Gesture Recognition of Transceiver-free Object by Using Wireless Networks

  • Zhang, Dian;Zheng, Weiling
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.10 no.2
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    • pp.787-806
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    • 2016
  • Traditional radio-based gesture recognition approaches usually require the target to carry a device (e.g., an EMG sensor or an accelerometer sensor). However, such requirement cannot be satisfied in many applications. For example, in smart home, users want to control the light on/off by some specific hand gesture, without finding and pressing the button especially in dark area. They will not carry any device in this scenario. To overcome this drawback, in this paper, we propose three algorithms able to recognize the target gesture (mainly the human hand gesture) without carrying any device, based on just Radio Signal Strength Indicator (RSSI). Our platform utilizes only 6 telosB sensor nodes with a very easy deployment. Experiment results show that the successful recognition radio can reach around 80% in our system.

Activity Object Detection Based on Improved Faster R-CNN

  • Zhang, Ning;Feng, Yiran;Lee, Eung-Joo
    • Journal of Korea Multimedia Society
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    • v.24 no.3
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    • pp.416-422
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    • 2021
  • Due to the large differences in human activity within classes, the large similarity between classes, and the problems of visual angle and occlusion, it is difficult to extract features manually, and the detection rate of human behavior is low. In order to better solve these problems, an improved Faster R-CNN-based detection algorithm is proposed in this paper. It achieves multi-object recognition and localization through a second-order detection network, and replaces the original feature extraction module with Dense-Net, which can fuse multi-level feature information, increase network depth and avoid disappearance of network gradients. Meanwhile, the proposal merging strategy is improved with Soft-NMS, where an attenuation function is designed to replace the conventional NMS algorithm, thereby avoiding missed detection of adjacent or overlapping objects, and enhancing the network detection accuracy under multiple objects. During the experiment, the improved Faster R-CNN method in this article has 84.7% target detection result, which is improved compared to other methods, which proves that the target recognition method has significant advantages and potential.

Improvement of self-mixing semiconductor laser range finder and its application to range-image recognition of slowly moving object

  • Suzuki, Takashi;Shinohara, Shigenobu;Yoshida, Hirofumi;Ikeda, Hiroaki;Saitoh, Yasuhiro;Nishide, Ken-Ichi;Sumi, Masao
    • 제어로봇시스템학회:학술대회논문집
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    • 1992.10b
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    • pp.388-393
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    • 1992
  • An infrared range finder using a self-mixing laser diode (SM-LD), which has been proposed and developed by the Authors, can measure not only a range of a moving target but its velocity simultaneously. In this paper, described is that the precise mode-hop pulse train can be obtained by employing a new signal processing circuit even when the backscattered light returning into the SM-LD is much more weaker. As a result, the distance to a tilted square sheet made from aluminium or white paper, which is placed 10 cm through 60 cm from the SM-LD, is measured with accuracy of a few percent even when the tilting angle is less than 75 degrees or 85 degrees, respectively. And in this paper, described is the range-image recognition of a plane object under the condition of standstill. The output laser beam is scanned by scanning two plane mirrors-equipped with each stepping motor. And we succeeded in the acquisition of the range-image of a plane object in a few tens of seconds. Furthermore, described is a feasibility study about the range-image recognition of a slowly moving plane object.

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The Bullet Launcher with A Pneumatic System to Detect Objects by Unique Markers

  • Jasmine Aulia;Zahrah Radila;Zaenal Afif Azhary;Aulia M. T. Nasution;Detak Yan Pratama;Katherin Indriawati;Iyon Titok Sugiarto;Wildan Panji Tresna
    • Journal of information and communication convergence engineering
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    • v.21 no.3
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    • pp.252-260
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    • 2023
  • A bullet launcher can be developed as a smart instrument, especially for use in the military section, that can track, identify, detect, mark, lock, and shoot a target by implementing an image-processing system. In this research, the application of object recognition system, laser encoding as a unique marker, 2-dimensional movement, and pneumatic as a shooter has been studied intensively. The results showed that object recognition system could detect various colors, patterns, sizes, and laser blinking. Measuring the average error value of the object distance by using the camera is ±4, ±5, and ±6% for circle, square and triangle form respectively. Meanwhile, the average accuracy of shots on objects is 95.24% and 85.71% in indoor and outdoor conditions respectively. Here, the average prototype response time is 1.11 s. Moreover, the highest accuracy rate of shooting results at 50 cm was obtained 98.32%.

Object Recognition Using Hausdorff Distance and Image Matching Algorithm (Hausdorff Distance와 이미지정합 알고리듬을 이용한 물체인식)

  • Kim, Dong-Gi;Lee, Wan-Jae;Gang, Lee-Seok
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.25 no.5
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    • pp.841-849
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    • 2001
  • The pixel information of the object was obtained sequentially and pixels were clustered to a label by the line labeling method. Feature points were determined by finding the slope for edge pixels after selecting the fixed number of edge pixels. The slope was estimated by the least square method to reduce the detection error. Once a matching point was determined by comparing the feature information of the object and the pattern, the parameters for translation, scaling and rotation were obtained by selecting the longer line of the two which passed through the matching point from left and right sides. Finally, modified Hausdorff Distance has been used to identify the similarity between the object and the given pattern. The multi-label method was developed for recognizing the patterns with more than one label, which performs the modified Hausdorff Distance twice. Experiments have been performed to verify the performance of the proposed algorithm and method for simple target image, complex target image, simple pattern, and complex pattern as well as the partially hidden object. It was proved via experiments that the proposed image matching algorithm for recognizing the object had a good performance of matching.

Objects Recognition and Intelligent Walking for Quadruped Robots based on Genetic Programming (4족 보행로봇의 물체 인식 및 GP 기반 지능적 보행)

  • Kim, Young-Kyun;Hyun, Soo-Hwan;Jang, Jae-Young;Seo, Ki-Sung
    • Journal of the Korean Institute of Intelligent Systems
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    • v.20 no.5
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    • pp.603-609
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    • 2010
  • This paper introduces an objects recognition algorithm based on SURF(Speeded Up Robust Features) and GP(Genetic Programming) based gaits generation. Combining both methods, a recognition based intelligent walking for quadruped robots is proposed. The gait of quadruped robots is generated by means of symbolic regression for each joint trajectories using GP. A position and size of target object are recognized by SURF which enables high speed feature extraction, and then the distance to the object is calculated. Experiments for objects recognition and autonomous walking for quadruped robots are executed for ODE based Webots simulation and real robot.