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

作者： Kyung-Joong Kim Sung-Bae Cho Department of Computer Science Yonsei University Seoul South Korea

There has been extensive research of developing the controller for a mobile robot. Especially, several researchers have constructed the mobile robot controller that can avoid obstacles, evade predators, or catch moving prey by evolutionary algorithms such as genetic algorithm and genetic programming. In this line of research, we have also developed a method of applying CAM-Brain, the evolved neural networks based on cellular automata, to control a mobile robot. However, the direct evolution has a difficulty that the controller cannot generalize well to new environments. We attempt to solve it by incremental evolution, which starts with simpler environments and gradually develops the controller with more general and complex environments. We combine several behaviors evolved or programmed by dynamic selection mechanism for higher behaviors. In this paper, we evaluate the robot performance by using the Khepera simulator. Simulation results show the possibility of easily developing higher behaviors by integrating the CAM-Brain behavior modules.

关键词： Mobile robots Biological neural networks Automatic control Neurons Robot control Biological cells Genetic algorithms Nerve fibers Neural networks Genetic programming

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Predicting combustion pressure of automobile engine employing chaos theory

Predicting combustion pressure of automobile engine employin...

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

作者： T. Iokibe Y. Fujimoto Computer System Business Unit Meidensha Corporation Chuo Tokyo Japan

Automobile manufacturers continue to put a large effort into developing low emission and fuel-efficient vehicles. One of the most important researches is to develop an engine that can work in the ideal combustion condition using fuel as little as possible. The air fuel ratio is reduced in order to realize high mileage. However, the exhaust gas condition may deteriorate or the engine stops, since the combustion condition becomes unstable. Therefore, high-precision predictive control of ignition timing and air fuel ratio are important in order to retain the engine performance. The preparation of the combustion model of the engine is indispensable for predictive control. But, because the combustion is nonlinear and complex, a practical combustion model is not yet developed. Chaos has been noticed as a theory that can treat nonlinear dynamical systems, and the research has energetically been advanced. For predicting the combustion condition of the automobile engine, we applied chaos theory. That is: the peak pressure of succeeding combustion is forecast, using only the combustion pressure time series of cylinders inside. In the paper, the purpose and results of research are reported.

关键词： Combustion Engines Chaos Fuels Predictive control Automobile manufacture Vehicles Ignition Timing Predictive models

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Backlash compensation by neural-network online learning

Backlash compensation by neural-network online learning

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

作者： Chao He Yuhe Zhang M. Meng Beijing Institute of Technology China Department of Electrical and Computer Engineering University of Alberta Canada

To eliminate the influences of backlash nonlinearity that generally exist in servo systems, a new neural-network online learning compensation method is presented. Not basing on the identification of backlash nonlinearity, the online learning of neural networks is used instead making the output error of the system approximate to zero so that the system output can accurately follow the given input. To cooperating with this new method, the self-organizing fuzzy CMAC with Gauss basis functions neural network is proposed on the basis of utilising the advantages of traditional CMAC neural networks, fuzzy logic, basis functions and the self-organizing feature map algorithm. Finally, an actual experimental platform of servo system with low power was built. The experimental results show that the method presented can effectively remove the limit cycle caused by the backlash nonlinearity, and greatly improve the system accuracy.

关键词： Neural networks Servomechanisms Limit-cycles Chaos Fuzzy logic Gears Electric motors Feedback control Neurofeedback Axles

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Modeling and analysis of dynamic multi-agent planar manipulation

Modeling and analysis of dynamic multi-agent planar manipula...

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

作者： Qingguo Li S. Payandeh Experimental Robotics Laboratory (ERL) School of Engineering Science Simon Fraser University Burnaby BC Canada

A dynamic model for multi-agent manipulation is investigated under a nonlinear control framework. The motion of the rigid body on a plane under two-finger pushing is modeled as a nonlinear system. The local controllability is derived for different cooperation patterns. The motion of the rigid body under pushing is composed of two stages: during the first stage, the fingers maintain contact with the object, and through adjusting the pushing position, orientation and force on the object, the configuration of the object can reach some subsets in configuration space. Due to local contact constraints, the fingers may lose contact with the object where the second stage of motion starts. Here, the motion of the object is governed by the friction force only. Thus manipulation planning consists of two parts. First, an initial state response problem needs to be solved to find the subset of configuration space which can reach the final configuration under the friction-governed sliding. The remaining problem can be categorized as optimal control problem, which solves the cooperation between agents which force the object moving into the subset found by the initial state response problem. The possibility of cooperation is illustrated through an example.

关键词： Manipulator dynamics Robot kinematics Fingers Laboratories Nonlinear systems Nonlinear dynamical systems control system analysis Nonlinear control systems control theory controllability

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Trajectory planning of mobile robots using DNA computing

Trajectory planning of mobile robots using DNA computing

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

作者： K. Kiguchi K. Watanabe T. Fukuda Department of Advanced Systems Control Engineering Saga University Saga Saga Japan Center of Cooperative Research in Advanced Science and Technology University of Nagoya Nagoya Japan

Recently, DNA computers attract attention as computers of next generation taking over the present electronic computers. Computation can be realized by chemical reaction of DNA. This paper presents an optimal trajectory planning method of mobile robots using DNA computing. In this method, a working area of a mobile robot is divided into many sections. Then the shortest trajectory avoiding obstacles in the work area is calculated with DNA computing. The location of the obstacles is supposed to be known in advance. In the process of DNA computing, Watson-Crick pairing is performed to find the shortest trajectory in the working area. The DNA sequences representing the locations of the obstacles are removed in this process. The obtained shortest DNA molecule that begins with the start section and terminates with the goal section represents the shortest trajectory avoiding the obstacles in the work area of the mobile robot. The proposed algorithm is especially effective on a DNA molecular computer.

关键词： Trajectory Mobile robots DNA computing Sequences Annealing control engineering Electronic mail Intelligent robots Chemical technology Technology planning

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Robot formations using only local sensing and control

Robot formations using only local sensing and control

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

作者： J. Fredslund M.J. Mataric Computer Science Department Aarhus University Denmark Interaction Lab Computer Science Department University of Southern California Los Angeles CA USA

We study the problem of achieving global behavior in a group of robots using only local sensing and interaction, in the context of formations, where the goal is to have N mobile robots establish and maintain some predetermined geometric shape. We have devised a simple, general, robust, localized, behavior-based algorithm that solves the problem for N robots each equipped with sonar, laser, camera, and a radio link for communicating with other robots. The method uses the idea of keeping a single friend at a desired angle (by panning the camera and keeping the friend centered in the image), and only communicating heartbeat messages. We also developed a general analytical method for evaluating formations and applied it to our algorithm. We validate our algorithm both in simulation and with physical robots.

关键词： Robot sensing systems Mobile robots Robot vision systems Cameras Context Shape Robustness Sonar Radio link Heart beat

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Real-time collision-free path planning and tracking control of a nonholonomic mobile robot using a biologically inspired approach

Real-time collision-free path planning and tracking control ...

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

作者： S.X. Yang Guangfeng Yuan M. Meng School of Engineering University of Guelph Guelph ONT Canada Department of Electrical and Computer Engineering University of Alberta Edmonton AB Canada

In this paper, a novel biologically inspired neural network approach is proposed for dynamic collision-free path planning and tracking control of a nonholonomic mobile robot in a nonstationary environment. The real-time collision-free trajectory of the mobile robot with obstacle avoidance is generated by a topologically organized neural network, where the dynamics of each neuron is characterized by a shunting equation derived from Hodgkin and Huxley's biological membrane equation. The configuration space of the mobile robot constitutes the state space of the neural network. The varying environment is represented by the dynamic activity landscape of the neural network, where the neural activity propagation is subject; to the kinematic constraint of the nonholonomic mobile robot. Thus no local collision checking procedures are needed. The tracking velocities are generated by a novel neural dynamics based controller, which is based on two shunting models and the conventional backstepping technique. Unlike the backstepping controllers that produce velocity commands with sharp jumps, the proposed tracking controller can generate smooth, continuous commands, not suffering from the velocity jump problem. The effectiveness and efficiency of the proposed approach are demonstrated through simulation and comparison studies.

关键词： Path planning Biological control systems Mobile robots Neural networks Velocity control Equations Backstepping Character generation Neurons Biomembranes

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A study on the interface of the Internet-based teleoperation

A study on the interface of the Internet-based teleoperation

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

作者： P.X. Liu M.Q.-H. Meng J.J. Gu Department of Electrical & Computer Engineering University of Alberta Edmonton AB Canada Department of Electrical and Computer Engineering Dalhousie University Halifax NS Canada

Most traditional teleoperation systems adopt a bilateral master-slave structure based on haptic interface devices to render torque/force feedback and generate commands to remote robots. Haptic interface devices with force-reflection are usually bulky, expensive and purpose-specific, which bring up incompatibility and unavailability problems. Furthermore, haptic interface devices introduce contact instability in the Internet based teleoperation with unbounded and random time delays. In the paper, instead of using traditional haptic interface devices, the concept "SoftHaptics" is introduced. The essence of SoftHaptic interfaces is to use visual cues and/or tonal cues to interpret sensed data feedback from remote robotic systems with which the operator can construct the same mental image of what happens there as using haptic interface devices. By using SoftHaptic interfaces, the unavailability and incompatibility of haptic interface devices can be avoided. Also, because there are no direct force interactions (no energy coupling) between the operator and the remote robot, there is no operator-induced instability.

关键词： Haptic interfaces Delay effects Master-slave Humans Reflection Force control Force feedback Robots Web and internet services Communication system control

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Frequency domain adaptive learning feedforward control

Frequency domain adaptive learning feedforward control

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

作者： YangQuan Chen K.L. Moore Center for Self-Organizing and Intelligent System (CSOIS) Department of Electrical and Computer Engineering UMC 4160 College of Engineering Utah State University Logan UT USA

A learning feedforward control (LFFC) acts as an "add-on" element to an existing feedback controller (FBC). The LFFC signal is updated iteratively based on the output of a B-splines network (BSN), with the FBC signal of previous iteration as its input. There are only two parameters to tune: the B-spline support width d and the learning gain /spl gamma/. Frequency stability analysis requires that d should be greater than a minimum value d/sub min/, which determines a cutoff frequency of the low pass learning filter. Using a fixed support d for all iterations and for all time at each iteration may be conservative and the actual feedforward signal may in fact contain frequencies higher than the cutoff frequency determined by d. This is the case when there are hard nonlinearities in the system. A frequency domain adaptive scheme is proposed in this paper where d is a time function and changes from iteration to iteration. A time-frequency representation (TFR) of feedback signal is constructed using WVD (Wigner-Ville distribution) and then its first order time moment is used to obtain the time-varying support d(t) via an iterative updating scheme based on the difference of the windowed tracking error root mean squares between two previous iterations. Detailed design procedures are given.

关键词： Frequency domain analysis Programmable control Adaptive control Cutoff frequency Spline Stability analysis Low pass filters Time frequency analysis Feedback Root mean square

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Moore automata for the supervisory control of robotic manufacturing workcells

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AUTONOMOUS ROBOTS 2000年第1期9卷 59-69页

作者： Ramirez-Serrano, A Zhu, SC Benhabib, B Univ Toronto Dept Mech & Ind Engn Comp Integrated Mfg Lab Toronto ON M5S 3G8 Canada

The potential of flexible-manufacturing workcells (FMCs) to produce a family of parts in many possible orders of operations and choices of different machines is advantageous. Despite intensive research on the theoretical control of discrete-event systems (DESs), however, current techniques can still only be used for the supervisory control of simple cells. In this paper, a novel modeling and control synthesis technique is presented for FMCs that allow part-routing flexibility. Our proposed methodology combines Extended Moore Automata (EMA) and controlled-Automata theories to synthesize supervisors for such FMCs.

关键词： flexible manufacturing workcells supervisory control Moore automata alternative processing routes

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