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2007 International Symposium on Computational Intelligence in Robotics and Automation最新文献

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Design and Development of a Biped Robot 双足机器人的设计与开发
2007 International Symposium on Computational Intelligence in Robotics and Automation Pub Date : 2007-06-20 DOI: 10.1109/CIRA.2007.382880
Vishnu V. Madadi, S. Tosunoglu
{"title":"Design and Development of a Biped Robot","authors":"Vishnu V. Madadi, S. Tosunoglu","doi":"10.1109/CIRA.2007.382880","DOIUrl":"https://doi.org/10.1109/CIRA.2007.382880","url":null,"abstract":"Many researchers have been encouraged to investigate the design, posture and stability of biped robots in order to replicate the anthropoid gait. This paper addresses the design and development of a bipedal robot. It presents a combination of the design considerations and simplicity of design to provide a test bed for autonomous biped robots. Kinematic models of the biped robot are also developed and simulated prior to experimentally verifying the performance of the system. Overall, a low cost, open system biped robot is the underlying objective on which new gait algorithms and controllers will be developed to further the research in the field of humanoid robots.","PeriodicalId":301626,"journal":{"name":"2007 International Symposium on Computational Intelligence in Robotics and Automation","volume":"415 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115925240","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 10
Adaptive Object Tracking using Particle Swarm Optimization 基于粒子群优化的自适应目标跟踪
2007 International Symposium on Computational Intelligence in Robotics and Automation Pub Date : 2007-06-20 DOI: 10.1109/CIRA.2007.382848
Yuhua Zheng, Y. Meng
{"title":"Adaptive Object Tracking using Particle Swarm Optimization","authors":"Yuhua Zheng, Y. Meng","doi":"10.1109/CIRA.2007.382848","DOIUrl":"https://doi.org/10.1109/CIRA.2007.382848","url":null,"abstract":"This paper presents an automatic object detection and tracking algorithm by using particle swarm optimization (PSO) based method, which is a searching algorithm inspired by the behaviors of social insect in the nature. A cascade of boosted classifiers based on Haar-like features is trained and employed to detect objects. To improve the searching efficiency, first the object model is projected into a high-dimensional feature space, and the PSO-based algorithm is applied to search over this high-dimensional space and converge to some global optima, which are well-matched candidates in terms of object features. Then, a Bayes-based filter is used to identify the best match with the highest possibility among these candidates under the constraint of object motion estimation. The proposed algorithm considers not only the object features but also the object motion estimation to speed up the searching procedure. Experimental results of tracking on vehicle and face demonstrate that the proposed method is efficient and robust under dynamic environment.","PeriodicalId":301626,"journal":{"name":"2007 International Symposium on Computational Intelligence in Robotics and Automation","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123724740","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 29
A Face Recognition System using Neural Networks with Incremental Learning Ability 具有增量学习能力的神经网络人脸识别系统
2007 International Symposium on Computational Intelligence in Robotics and Automation Pub Date : 2007-06-20 DOI: 10.1109/CIRA.2007.382904
Y. A. Ghassabeh, H. Moghaddam
{"title":"A Face Recognition System using Neural Networks with Incremental Learning Ability","authors":"Y. A. Ghassabeh, H. Moghaddam","doi":"10.1109/CIRA.2007.382904","DOIUrl":"https://doi.org/10.1109/CIRA.2007.382904","url":null,"abstract":"In this paper, we present a new incremental face recognition (IFR) system based on new adaptive learning algorithms and networks. We introduce new adaptive linear discriminant analysis (LDA) algorithm and related network for optimal facial feature extraction and use them to construct a new IFR system. Convergence proof of all algorithms is given using an appropriate cost function and discussing about its initial conditions. Application of the new IFR on feature extraction from facial image sequences is given in two steps: i) image preprocessing, which includes normalization, histogram equalization, mean centering and background removal, ii) adaptive LDA feature estimation. In the preprocessing stage, all input images are cropped and prepared for the next step. Outputs of the preprocessing stage are used as a sequence of inputs for IFR system. The proposed system was tested on YALE face database. Experimental results on this database demonstrated the effectiveness of the proposed system for adaptive estimation of the feature space for online face recognition.","PeriodicalId":301626,"journal":{"name":"2007 International Symposium on Computational Intelligence in Robotics and Automation","volume":"31 8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121705105","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 4
Catheter insertion path reconstruction with autonomous system for endovascular surgery 血管内手术中自主系统置管路径重建
2007 International Symposium on Computational Intelligence in Robotics and Automation Pub Date : 2007-06-20 DOI: 10.1109/CIRA.2007.382845
C. Tercero, S. Ikeda, T. Fukuda, K. Sekiyama, Y. Okada, T. Uchiyama, M. Negoro, I. Takahashi
{"title":"Catheter insertion path reconstruction with autonomous system for endovascular surgery","authors":"C. Tercero, S. Ikeda, T. Fukuda, K. Sekiyama, Y. Okada, T. Uchiyama, M. Negoro, I. Takahashi","doi":"10.1109/CIRA.2007.382845","DOIUrl":"https://doi.org/10.1109/CIRA.2007.382845","url":null,"abstract":"In order to reduce fluoroscope usage in endovascular surgery there is a need to develop autonomous catheter insertion systems. We propose a system for tracking the position of the catheter using a magnetic motion capture sensor to provide feedback to a catheter driving mechanism to perform autonomous catheter insertion in major vasculature. Catheter insertion path reconstruction experiments were performed with the system inside silicone model of major vasculature to simulate surgery. As result the system reproduced a path inside the silicone blood vessel phantom with less than 7 mm of error. We found that error in path reconstruction depends on the model's cross-section diameter, the properties of the catheter insertion mechanism, the magnetic sensor and the system guidance technique.","PeriodicalId":301626,"journal":{"name":"2007 International Symposium on Computational Intelligence in Robotics and Automation","volume":"97 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122576157","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 8
A comparative study of smooth path planning for a mobile robot by evolutionary multi-objective optimization 基于进化多目标优化的移动机器人平滑路径规划比较研究
2007 International Symposium on Computational Intelligence in Robotics and Automation Pub Date : 2007-06-20 DOI: 10.1109/CIRA.2007.382857
Kao-Ting Hung, Jing-Sin Liu, Yau-Zen Chang
{"title":"A comparative study of smooth path planning for a mobile robot by evolutionary multi-objective optimization","authors":"Kao-Ting Hung, Jing-Sin Liu, Yau-Zen Chang","doi":"10.1109/CIRA.2007.382857","DOIUrl":"https://doi.org/10.1109/CIRA.2007.382857","url":null,"abstract":"This paper studies the evolutionary planning strategies for mobile robots to move smoothly along efficient collision-free paths in known static environments. The cost of each candidate path is composed of the path length and a weighted sum of penetration depth to vertices of polygonal obstacles. The path is composed of a pre-specified number of cubic spiral segments with constrained curvature. Comparison of the path planning performance between two Pareto-optimal schemes, the parallel genetic algorithm scheme based on the island method (PGA) and the non-dominated sorting genetic algorithm (NSGA-II), are conducted in terms of success rate in separate runs and path length whenever collision-free paths are found. Numerical simulation results are presented for three types of obstacles: polygons, walls, and combinations of both.","PeriodicalId":301626,"journal":{"name":"2007 International Symposium on Computational Intelligence in Robotics and Automation","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129619932","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 18
Development of Control for a Serpentine Robot 蛇形机器人控制系统的研制
2007 International Symposium on Computational Intelligence in Robotics and Automation Pub Date : 2007-06-20 DOI: 10.1109/CIRA.2007.382868
William R. Hutchison, Betsy J. Constantine, Johann Borenstein, Jerry E. Pratt
{"title":"Development of Control for a Serpentine Robot","authors":"William R. Hutchison, Betsy J. Constantine, Johann Borenstein, Jerry E. Pratt","doi":"10.1109/CIRA.2007.382868","DOIUrl":"https://doi.org/10.1109/CIRA.2007.382868","url":null,"abstract":"This paper describes the development and testing of control of the OmniTread OT-4 robot by the seventh generation (7G) control system. Control of OT-4 was developed in the Yobotics 3D simulator by an iterative process combining genetic algorithm, learning and analytic programming techniques. The control system developed in simulation was tested by controlling the real OT-4 robot in the laboratory. The performance of the real OT-4 robot under 7G control on stairs, parallel bars, a slalom course, and stairs with obstacles corresponded well to the simulated performance on which development of the control system was based.","PeriodicalId":301626,"journal":{"name":"2007 International Symposium on Computational Intelligence in Robotics and Automation","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122509964","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 12
Genetic Algorithm Optimization in a Cognitive Radio for Autonomous Vehicle Communications 自动驾驶汽车认知无线电的遗传算法优化
2007 International Symposium on Computational Intelligence in Robotics and Automation Pub Date : 2007-06-20 DOI: 10.1109/CIRA.2007.382925
J. F. Hauris
{"title":"Genetic Algorithm Optimization in a Cognitive Radio for Autonomous Vehicle Communications","authors":"J. F. Hauris","doi":"10.1109/CIRA.2007.382925","DOIUrl":"https://doi.org/10.1109/CIRA.2007.382925","url":null,"abstract":"Autonomous vehicles travel through a varying environment that is not limited to the physical terrain but also includes the \"RF terrain\". The autonomous vehicle must be able to adapt to the varying RF conditions. \"Cognitive radios\" are being developed that address this issue. This paper discusses the use of genetic algorithms (GA) to implement the adaptive processes for a cognitive radio on an autonomous vehicle. Specifically GA's are used to solve the optimization of RF parameters for a wireless network. In particular, a fitness measure is derived which provides a figure of merit for the performance of the GA in relation to overall RF performance. Additionally, a chromosome structure is derived which consists of \"RF genes\". Each gene is a binary string representing some aspect or parameter of the RF environment. Finally the GA determines a set of RF parameters for optimal radio communications in the varying RF environment.","PeriodicalId":301626,"journal":{"name":"2007 International Symposium on Computational Intelligence in Robotics and Automation","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125988474","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 33
A simple rule how to make a reward for learning with human interaction 这是一个简单的规则，如何通过人际互动来奖励学习
2007 International Symposium on Computational Intelligence in Robotics and Automation Pub Date : 2007-06-20 DOI: 10.1109/CIRA.2007.382921
K. Kurashige
{"title":"A simple rule how to make a reward for learning with human interaction","authors":"K. Kurashige","doi":"10.1109/CIRA.2007.382921","DOIUrl":"https://doi.org/10.1109/CIRA.2007.382921","url":null,"abstract":"Various learning methods are adapted for experimental robot. We can make movement of a robot by giving teaching signals to a robot. But it is heavy for operator to define how to give teaching signals generally because operator must guess and think of a task and environment and define a function to do that. Here the author aim to create teaching signals automatically for each task and environment. In this paper, the author suggest a simple rule which is independent of information about any task and environment to create teaching signals for each task and environment. This rule is that a situation which is often happened is good situation. In this paper, the author adopt reinforcement learning as learning method and a small-sized humanoid robot as application. The author show creating a reward by adapting a rule and show that a robot can learn and make movement.","PeriodicalId":301626,"journal":{"name":"2007 International Symposium on Computational Intelligence in Robotics and Automation","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127731105","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Robot Self-Localization based on a Single Image of Identified Landmarks 基于单幅地标识别图像的机器人自定位
2007 International Symposium on Computational Intelligence in Robotics and Automation Pub Date : 2007-06-20 DOI: 10.1109/CIRA.2007.382903
Wenfei Liu, Yu Zhou
{"title":"Robot Self-Localization based on a Single Image of Identified Landmarks","authors":"Wenfei Liu, Yu Zhou","doi":"10.1109/CIRA.2007.382903","DOIUrl":"https://doi.org/10.1109/CIRA.2007.382903","url":null,"abstract":"This paper introduces a novel self-localization algorithm for mobile robots, which recovers the robot position from a single image of identified landmarks taken by an onboard camera. The visual angle between two landmarks can be derived from their projections in the same image. The distances between the optical center and the landmarks can be calculated from the visual angles and the known landmark positions based on the law of cosine. The robot position can then be determined using the principle of trilateration. Extensive simulation has been carried out. A comprehensive error analysis provides the insight on how to improve the localization accuracy.","PeriodicalId":301626,"journal":{"name":"2007 International Symposium on Computational Intelligence in Robotics and Automation","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132691240","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 6
Object Tracking by introducing Stochastic Filtering into Window-Matching Techniques 将随机滤波引入窗口匹配技术的目标跟踪
2007 International Symposium on Computational Intelligence in Robotics and Automation Pub Date : 2007-06-20 DOI: 10.1109/CIRA.2007.382869
F. Vidal, V. Alcalde
{"title":"Object Tracking by introducing Stochastic Filtering into Window-Matching Techniques","authors":"F. Vidal, V. Alcalde","doi":"10.1109/CIRA.2007.382869","DOIUrl":"https://doi.org/10.1109/CIRA.2007.382869","url":null,"abstract":"This paper describes the development and the application of an object tracking algorithm from a sequence of images. The algorithm is based on window-matching techniques using the sum of squared differences (SSD) as a distance-similarity measure, but adding stochastic filtering. The algorithm is then applied for tracking a vehicle on an urban environment and for tracking the ball on a ping-pong game. It is concluded that incorporating the Kalman filtering greatly improves the tracking performance.","PeriodicalId":301626,"journal":{"name":"2007 International Symposium on Computational Intelligence in Robotics and Automation","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127972637","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
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