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Automatic programming of a time-optimal robot controller and an analog electrical circuit to implement the robot controller by means of genetic programming

Automatic programming of a time-optimal robot controller and...

引用

ieee International symposium on computational intelligence in Robotics and automation (CIRA)

作者： J.R. Koza F.H. Bennett M.A. Keane D. Andre Computer Science Department University of Stanford Stanford CA USA Visiting Scholar Computer Science Department University of Stanford Stanford CA USA Martin Keane Inc. Chicago IL USA Computer Science Division University of California Berkeley CA USA

Genetic programming is an automatic programming technique that evolves computer programs to solve, or approximately solve, problems. This paper presents two examples in which genetic programming creates a computer program for controlling a robot so that the robot moves to a specified destination point in minimal time. In the first approach, genetic programming evolves a computer program composed of ordinary arithmetic operations and conditional operations to implement a time-optimal control strategy. In the second approach, genetic programming evolves the design of an analog electrical circuit consisting of transistors, diodes, resistors, and power supplies to implement a near-optimal control strategy.

关键词： Automatic programming Robotics and automation Automatic control Robot control Genetic programming Digital arithmetic Circuits Diodes Resistors Power supplies

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Genetic algorithms for adaptive motion planning of an autonomous mobile robot

Genetic algorithms for adaptive motion planning of an autono...

引用

ieee International symposium on computational intelligence in Robotics and automation (CIRA)

作者： K. Sugihara J. Smith Department of Information and Computer Science University of Hawaii Manoa Honolulu HI USA

This paper proposes genetic algorithms (GAs) for path planning and trajectory planning of an autonomous mobile robot. Our GA-based approach has an advantage of adaptivity such that the GAs work even if an environment is time-varying or unknown. Therefore, it is suitable for both off-line and online motion planning. We first present a GA for path planning in a 2D terrain. Simulation results on the performance and adaptivity of the GA on randomly generated terrains are presented. Then, we discuss extensions of the GA for solving both path planning and trajectory planning simultaneously.

关键词： Genetic algorithms Motion planning Mobile robots Path planning Trajectory Intelligent control US Department of Commerce Solids Costs

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3D-icon based user interaction for robot programming by demonstration

3D-icon based user interaction for robot programming by demo...

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ieee International symposium on computational intelligence in Robotics and automation (CIRA)

作者： H. Friedrich H. Hofmann R. Dillmann Inst. for Real-Time Comput. Syst. & Robotics Karlsruhe Univ. Germany Institute for Real-Time Computer Systems & Robotics IPR University of Karlsruhe Karlsruhe Germany

Within the last years the programming by demonstration (PbD) programming methodology gained more and more attention in robotics. However, a high quality way of human-robot interaction is crucial for a successful application of the PbD methodology in robotics. Hypotheses derived from the programming system, and control knowledge included in a generated robot program has to be checked back with and to be verified by the user in order to avoid potentially harmful errors that lead to faulty code. This paper describes a method for user-robot interaction that is based on 3D-icons and supports and facilitates the programming process in a robot programming by demonstration system significantly.

关键词： Robot programming Service robots Robot sensing systems control systems Sensor systems Humans Robustness Real time systems Intellectual property Electronic mail

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Region-based Q-learning for intelligent robot systems

Region-based Q-learning for intelligent robot systems

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ieee International symposium on computational intelligence in Robotics and automation (CIRA)

作者： I.H. Suh J.H. Kim S.R. Oh Intelligent Control and Robotics Laboratory Department of Electronics Eng Hanyang University Kyunggi South Korea

It is desirable for autonomous robot systems to possess the ability to behave in a smooth and continuous fashion when interacting with an unknown environment. Since Q-learning requires a lot of memory and time to optimize a series of actions in a continuous state space, it may not be easy to apply the method to such a real environment. In this paper, for a continuous state space application, we propose a new method of Q-learning that incorporates a region-based reward assignment being used to solve a structural credit assignment problem and a triangular type Q-value model. Our learning method can estimate a current Q-value by a relationship with its neighboring states and has the ability to learn its actions similar to that of Q-learning. Thus, our method can enable robots to move smoothly in a real environment. To show the validity of our method, navigation comparison with Q-learning is given and visual tracking simulation results involving a 2-DOF SCARA robot are also presented.

关键词： Intelligent robots State-space methods Learning systems Navigation Intelligent control Orbital robotics Optimization methods State estimation control systems Fuzzy sets

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Action selection mechanism for soccer robot

Action selection mechanism for soccer robot

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ieee International symposium on computational intelligence in Robotics and automation (CIRA)

作者： Heung-Soo Kim Hyun-Sik Shim Myung-Jin Jung Jong-Hwan Kim Department of Electrical Engineering KAIST South Korea

ISBN: (纸本)0818681381

In this paper, an action selection mechanism (ASM) is proposed for each agent given its role in a multiagent system for robot soccer. The robot soccer game has very dynamic and uncertain characteristics. Furthermore, there exist competitions between agents. The soccer-playing robot should take an appropriate action according to its given role such as striker or sweeper. A computational mechanism for such action selection is essential in this regard. Initially, a relatively simple ASM is designed for a situation with no opponents. Then, the mechanism incorporates some additional action selection schemes considering the opponents' behaviors. Particularly, a multilayer perceptron (MLP) is used to learn how a human being selects an action given a situation. The effectiveness of the proposed ASM is demonstrated through a real robot soccer game of S-MIROSOT (single-robot micro-robot world cup soccer tournament).

关键词： Game theory Robot sensing systems Humans Robot vision systems Nonhomogeneous media Computer architecture Neural networks Computer simulation Distributed control Decision making

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Integrative architecture of the autonomous hand-eye robot JANUS

Integrative architecture of the autonomous hand-eye robot JA...

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ieee International symposium on computational intelligence in Robotics and automation (CIRA)

作者： G. Richter F. Smieja U. Beyer RIICP Theoretical Foundation GMD Laboratory Institute for System Design Technology German National Research Center for Information Technology (GMD) Sankt Augustin Germany

The importance of a good architectural design is often overlooked in the furor and excitement of new-age task-motivated and reactive robot construction. However the lack of a good architecture will often prove to be a weak link in an otherwise successful prototype, especially when development reaches the interesting stage of extension to more general functionality, or the introduction of adaptivity and higher-level control loops. In this article we describe various aspects of the architecture underlying our hand-eye reactive robot JANUS. The architecture allows at every level the introduction of functionality extensions and adaptivity. Furthermore, the intrinsic parallelism of the architecture enables easy porting from a single host computer to one or more computer clusters to produce immediate and significant operation speed-up. A central characteristic of the architecture is its integrative nature. This is illustrated by the way in which autonomous components dealing with motorics and sensorics can exchange information and work actively with each other.

关键词： Computer architecture control systems Laboratories Information technology Prototypes Robot sensing systems Force sensors Robustness Electronic switching systems Intelligent robots

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On the tuning of the free parameters of a new adaptive robot control based on geometric principles of Hamiltonian mechanics

On the tuning of the free parameters of a new adaptive robot...

引用

ieee International symposium on computational intelligence in Robotics and automation (CIRA)

作者： J.K. Tar I.J. Rudas J.F. Bito O.M. Kaynak Department of Information Technology Bánki Donát Polytechnic Budapest Hungary Bánk Donát Polytechnic Centre of Robotics and Automation Budapest Hungary UNESCO Chair of Mechatronics Bogazici University Istanbul Turkey

A novel approach toward the adaptive control of robots dynamically interacting with an unmodelled environment and having only approximately known dynamic parameters has previously been developed on the basis of the principles of the Hamiltonian mechanics. Like different means of modern soft computing technology such as artificial neural networks (ANNs) or fuzzy controllers having a more or less uniform architecture independent of the particular details of the problems to be solved by them, the proposed method also has a uniform structure not strictly tailored to the peculiar properties of the mechanical system to be controlled. However, as special kinds of ANNs are fit to solve wide but typical classes of tasks the proposed method is invented for tackling problems related to the control of mechanical devices in which the dominating nonlinear coupling originates from the laws of classical mechanics. As ANNs have plenty of free parameters (connection weights and threshold values) the tuning of which means learning, this mechanical model also contains tunable parameters so offering the possibility for learning. In this paper the model's free parameters, possible constraints imposed on them as well as different tuning strategies are discussed partly on the basis of computer simulations.

关键词： Robots control systems Adaptive control Artificial neural networks Fuzzy control Fuzzy neural networks Fuzzy systems Computer architecture Mechanical factors Mechanical systems

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Learning strategies for sensor-based manipulation tasks

Learning strategies for sensor-based manipulation tasks

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ieee International symposium on computational intelligence in Robotics and automation (CIRA)

作者： E. Cervera A.P. de Pobil Department of Computer Science Jaume I University Castellon Spain

An architecture that incorporates a seamless integration of different learning paradigms is presented. Sensor processing, recurrent neural networks, learning from experience and qualitative knowledge are the key elements of the system. The goal applications are those tasks which cannot be fully programmed due to uncertainties and incomplete knowledge. The proposed sensor-based architecture combines several learning paradigms as well as pre-programmed modules, since experimental evidence suggests that some paradigms are more convenient for learning certain skills. The correspondence between qualitative states and actions is learnt. The qualitative treatment of information makes it suitable for the analysis of system behavior, knowledge extraction and generalization to other more complex tasks. Programming is used to decrease the complexity of the learning process. This general approach is a suitable scheme for a wide range of robot situations. Results are provided for the simulation of a sensor-based goal-finding task as well as for a real application of the architecture in a robotic insertion process in three dimensions.

关键词： Robot sensing systems Uncertainty Recurrent neural networks Data mining Robustness Motion control Computer science Computer architecture Sensor systems Application software

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A new straight edge detection algorithm using direction-controlled edge tracking and random hitting

A new straight edge detection algorithm using direction-cont...

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ieee International symposium on computational intelligence in Robotics and automation (CIRA)

作者： K.A. Morsy Y. Kanayama Department of Computer Science Naval Postgraduate School Monterrey CA USA

This paper presents a new efficient straight edge detection algorithm for autonomous robot navigation and other visual tasks. First, we propose a new edge tracking algorithm that gives the endpoints of the detected edge. To obtain robust edge directions we use a least-squares linear fitting method to control the tracking process. Based on this "direction-controlled" edge tracking method, we construct an algorithm to find all major edges in an image. To minimize the exhaustive pixel processing, we adopt a random hitting method using a pseudo random number generator. Only if an initial pixel generated is significant, we track the edge that the pixel belongs to. To avoid finding the same segment twice, we examine whether a newly generated pixel is close to any of the already detected segments. Through our experiments we confirmed that most of major edges are detected by processing of an extremely small fraction of the total pixels. Only by processing of 4.36% of the total pixels we were able to detect 20 major line segments in a test image. Therefore, implementing this algorithm will be extremely effective in image understanding and visual applications including the model-based real-time robot navigation task.

关键词： Image edge detection Image segmentation Robots Testing Navigation Pixel Computer science Robust control Random number generation Object recognition

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A hierarchical, automated target recognition algorithm for a parallel analog processor

A hierarchical, automated target recognition algorithm for a...

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ieee International symposium on computational intelligence in Robotics and automation (CIRA)

作者： C. Padgett G. Woodward Jet Propulsion Laboratory California Institute of Technology Pasadena CA USA

A hierarchical approach is described for an automated target recognition (ATR) system, VIGILANTE, that uses a massively parallel, analog processor (3DANN). The 3DANN processor is capable of performing 64 concurrent inner products of size 1/spl times/4096 every 250 nanoseconds. A complete 64/spl times/64 raster scan of a 256/spl times/256 image can be evaluated by the 3DANN with its 64 modifiable templates in about 16 milliseconds. To fully utilize the analog processor and accommodate its high bandwidth capabilities, the vectors (templates) loaded on the 3DANN perform dimensionality reduction for a backend set of classifiers. The templates used in this ATR algorithm are hierarchically generated sets of eigenvectors taken from a partitioned set of library object images. As information is accumulated about the target (e.g. object class), a more refined set of eigenvectors reflecting this knowledge can be loaded and more specialized classifiers utilized. The classifiers provide information related to the ATR task: location, class, sub-class, and orientation of target(s). We report some preliminary results that examine the performance of orientation classifiers. With no knowledge about object class or orientation, a neural network achieves 94.2% in determining to which one of three classes from vertical (30/spl deg/, 45/spl deg/, or 60/spl deg/) an object image is oriented (/spl plusmn/30/spl deg/). Using an eigenvector template set generated from a distribution where both object class and orientation are known, a neural network classifier achieves 96% in orienting the object to within /spl plusmn/22.5/spl deg/. This information can be used to load even more specific eigenvector sets which should lead to more accurate object location during tracking and an enhancement in object recognition tasks.

关键词： Target recognition Optical sensors Neural networks Target tracking High speed optical techniques Charge-coupled image sensors Optical control Image sensors Sensor systems Optical imaging

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