{"title":"Analysis of image sequences to determine rotational and translational parameters","authors":"G. Tseng, A. Sood","doi":"10.1109/ISIC.1988.65426","DOIUrl":"https://doi.org/10.1109/ISIC.1988.65426","url":null,"abstract":"An approach for analyzing image sequences for motion parameter estimation is presented. A sequence of an arbitrary number of image frames is utilized to determine rotational and translational parameters. A dynamic scene model is developed in which image sequences are processed as a temporally correlated complex. The object motion is represented as a discrete-time time-varying system. The measurement consists of a sequence of image coordinates of three or more feature points in each frame. Using this model, measurement of the position of the object in a set of consecutive frames permits the estimation of motion as a function of time. An iterative parameter estimation technique is used to minimize the projection error. The technique is based on results from optimal control theory. Motion parameters are estimated from the sequences of image correspondences by modeling the motion dynamics using motion transformation and viewing projection. This methodology is suitable for processing a long sequence in situations where a high rate of imagery is available. Results are presented for general rigid-body motion in the context of synthesized images and real robot images.<<ETX>>","PeriodicalId":155616,"journal":{"name":"Proceedings IEEE International Symposium on Intelligent Control 1988","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1988-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132590139","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}
A. de Almeida, H. Fachada, J. Dias, P. Amado, P. Menezes, U. Nunes
{"title":"Low-cost, high performance servo-pneumatic manipulators with sensor feedback","authors":"A. de Almeida, H. Fachada, J. Dias, P. Amado, P. Menezes, U. Nunes","doi":"10.1109/ISIC.1988.65476","DOIUrl":"https://doi.org/10.1109/ISIC.1988.65476","url":null,"abstract":"New types of manipulators featuring both low cost and flexibility are required to expand the spectrum of applications in factory automation for assembly purposes. A low-cost manipulator which uses pneumatic cylinders as the actuators is described. The cylinders do not require any gearboxes and are fitted with incremental encoders for continuous position monitoring. Continuous positioning of the manipulator axes is achieved through proportional pneumatic valves driven by a hierarchical control structure. This distributed structure also simplifies the integration of the sensors required for each particular application. A machine vision system based on the use of fast digital signal processors was developed, providing additional sensory feedback. To overcome the problems associated with the highly nonlinear nature of the system composed by the proportional valves and the pneumatic cylinders, both variable structure control algorithms and proportional-integral-derivative algorithms are used to achieve an optimal response.<<ETX>>","PeriodicalId":155616,"journal":{"name":"Proceedings IEEE International Symposium on Intelligent Control 1988","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1988-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116747984","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}
C. R. Brittain, P.J. Otaduy, L. Rovere, R. B. Perez
{"title":"A new approach to hierarchical decomposition of large scale systems","authors":"C. R. Brittain, P.J. Otaduy, L. Rovere, R. B. Perez","doi":"10.1109/ISIC.1988.65414","DOIUrl":"https://doi.org/10.1109/ISIC.1988.65414","url":null,"abstract":"A technique for the hierarchical decomposition of large-scale systems is proposed. It results in a noniterative scheme for near-optimal control of both linear and nonlinear large-scale systems. In this approach, the role of the coordinator module is that of a supervisory controller whose task is to establish the strategy for distributing the overall system demands among each of the subsystems according to their performance and plant status. Each subsystem's controller relays in optimal control algorithms based on uncertain dynamics methods. The solution to each subsystem's optimal control problem is based on Pontryagin's maximum principle and the time-reversal paradigm for free-terminal-time problems. This approach transforms the two-point boundary value problem into an initial value problem which permits integration of both the state and adjoint equations forward in time. For those control problems for which the two-point boundary value formulation can be transformed into an initial value case, this approach will permit online implementation of nonlinear hierarchical controllers for large-scale systems.<<ETX>>","PeriodicalId":155616,"journal":{"name":"Proceedings IEEE International Symposium on Intelligent Control 1988","volume":"101 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1988-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132250907","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}
{"title":"A review of artificial intelligence in feedback control","authors":"D.G. Karetnyk, E. Grant, D.R. McGregor","doi":"10.1109/ISIC.1988.65402","DOIUrl":"https://doi.org/10.1109/ISIC.1988.65402","url":null,"abstract":"The use of knowledge-based techniques in feedback control is reviewed. Fuzzy linguistic control, qualitative causal control, and procedural control, as well as reinforcement learning and induction, are discussed. A brief comparison of these techniques in terms of some key characteristics is presented.<<ETX>>","PeriodicalId":155616,"journal":{"name":"Proceedings IEEE International Symposium on Intelligent Control 1988","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1988-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132813381","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}
{"title":"Automated assembly in the presence of significant system errors","authors":"Erik Vaaler, W. Seering","doi":"10.1109/ISIC.1988.65454","DOIUrl":"https://doi.org/10.1109/ISIC.1988.65454","url":null,"abstract":"A primary source of difficulty in automated assembly is the uncertainty in the relative position of the parts being assembled. A logic branching approach to solving this problem is discussed. Force sensor information, responses to recent moves, and results from previous assemblies are used to generate the branching decisions. Several heuristic assembly algorithms are presented. The proposed approach generates efficient compliant motion strategies for any set of hard, smooth parts that can be modeled as a peg and hole. Two of the algorithms converge to acceptable performance levels in less than 100 assembly trials. This implies that a real assembly cell using these algorithms would converge quickly enough for the learning to be done online. This would eliminate the modeling errors introduced by learning with an assembly simulator. Logic branching is compared with other machine learning and expert system techniques.<<ETX>>","PeriodicalId":155616,"journal":{"name":"Proceedings IEEE International Symposium on Intelligent Control 1988","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1988-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129339280","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}
{"title":"A corner detection-based object representation technique for 2-D images","authors":"R. Bachnak, M. Celenk","doi":"10.1109/ISIC.1988.65428","DOIUrl":"https://doi.org/10.1109/ISIC.1988.65428","url":null,"abstract":"A corner detection-based object representation technique that operates on a thinned binary image is presented. The proposed method consists of two computational phases. The first phase involves the use of a corner detection method which detects the corners in the image. The second phase is a curve-following process that establishes the topological relationships between the corners for a complete object representation. The final output of the method is a list of corners, each identified by its position, the number of its edges, and the neighboring corners connected to it. Experimental results on a computer-generated line-drawing and an image of a real object are presented. The method gives reasonably good results for the images used in the test experiments.<<ETX>>","PeriodicalId":155616,"journal":{"name":"Proceedings IEEE International Symposium on Intelligent Control 1988","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1988-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125704380","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}
{"title":"A stepwise evolutionary approach to machine learning","authors":"K. Hintz","doi":"10.1109/ISIC.1988.65491","DOIUrl":"https://doi.org/10.1109/ISIC.1988.65491","url":null,"abstract":"The biological concepts of stepwise evolution and cumulative selection are used to develop programs for a digital computer. The initial goal of these programs is to separate small, two-dimensional arrays of binary valued patterns into two classes. Learning is accomplished by the automatic evaluation of a criterion of separability of the two classes for each of the possible single-step mutations of the initial classification program. The mutant program which performs best is then selected automatically by the environment program and used as the new classification program. Only four operations are initially available, but as each classification program is mutated and cumulatively selected based on its performance, a new classification program is developed for implementing this particular classification. Each resulting program is then assigned a next sequential number, stored in mass storage, and made available for use as a single program step by subsequent programs. As the development program is run, it not only learns how to dichotomize more patterns but also has available to it the results of previous evolutionary learning experiences.<<ETX>>","PeriodicalId":155616,"journal":{"name":"Proceedings IEEE International Symposium on Intelligent Control 1988","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1988-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125797623","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}
{"title":"Application of heuristic search and information theory to sequential fault diagnosis","authors":"K. Pattipati, M. G. Alexandridis","doi":"10.1109/ISIC.1988.65446","DOIUrl":"https://doi.org/10.1109/ISIC.1988.65446","url":null,"abstract":"The problem of constructing optimal and near-optimal test sequences to diagnose permanent faults in electronic and electromechanical systems is considered. The test sequencing problem is formulated as an optimal binary AND/OR decision tree construction problem, whose solution is known to be NP-complete. The approach is based on integrating concepts from information theory and heuristic AND/OR graph search methods to subdue the computational explosion of the optimal test sequencing problem. Lower bounds on the optimal cost-to-go are derived from the information-theoretic concepts of Huffman coding and entropy, which ensure that an optimal solution is found using the heuristic AND/OR graph search algorithms. This makes it possible to obtain optimal test sequences to problems that are intractable with the traditional dynamic programming techniques. In addition, a class of test sequencing algorithms that provide a tradeoff between optimality and complexity have been derived using the epsilon -optimal and limited search strategies. The effectiveness of the algorithms is demonstrated on several test cases. As a by-product, this approach to test sequencing can be adapted to solve a wide variety of binary identification problems arising in other fields.<<ETX>>","PeriodicalId":155616,"journal":{"name":"Proceedings IEEE International Symposium on Intelligent Control 1988","volume":"106 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1988-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124059819","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}
{"title":"Genetic algorithms in system identification","authors":"K. Kristinsson, G. Dumont","doi":"10.1109/ISIC.1988.65498","DOIUrl":"https://doi.org/10.1109/ISIC.1988.65498","url":null,"abstract":"Current online identification techniques are recursive and local search techniques. In the present work, it is shown how genetic algorithms, a parallel, global search technique emulating natural genetic operators, can be used to estimate the poles and zeros of a dynamical system. An adaptive controller is designed on the basis of the estimates. Simulations and an experiment show the technique to be satisfactory and to provide unbiased estimates in the presence of colored noise.<<ETX>>","PeriodicalId":155616,"journal":{"name":"Proceedings IEEE International Symposium on Intelligent Control 1988","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1988-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124075803","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}
{"title":"Fusion of range and reflectance image data using Markov random fields","authors":"G. Bilbro, W. Snyder","doi":"10.1109/ISIC.1988.65422","DOIUrl":"https://doi.org/10.1109/ISIC.1988.65422","url":null,"abstract":"The problem of fusion of range and luminance data is addressed. Fusion is accomplished by minimization of an objective function which requires that the observed brightness agree with both the observed range image and a reflectivity model. The performance of this technique is evaluated.<<ETX>>","PeriodicalId":155616,"journal":{"name":"Proceedings IEEE International Symposium on Intelligent Control 1988","volume":"180 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1988-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128827767","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}