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International Joint Conference on Neural Networks (IJCNN)

作者： Xiangui Yu N.K. Loh W.C. Miller Department of Electrical Engineering University of Windsor Windsor ONT Canada Center for Robotics and Advanced Automation Dodge Hall of Engineering Oakland University Rochester MI USA

This paper presents one kind of modified backpropagation algorithm for training the multilayer feedforward neural networks with hard-limiting neurons. Adaptive steepness factors in the analog sigmoidal neuron activation functions are updated in the training process. With the decrease of the sum-square error, these steepness factors are varied from a small positive value to infinite. It makes the sigmoidal neuron transferred to hard-limiting one after the training process complete. Thus, a multilayer feedforward neural network can be trained with the resultant architecture is only composed of hard-limiting neurons. The learning algorithm is similar to the conventional backpropagation algorithm, only the derivatives of the hidden neural activation functions are modified according to the proposed idea. Extensive numerical simulations are presented to show the feasibility of the proposed algorithm. In addition, the numerical properties of the proposed algorithm are also discussed in detail. Comparisons of the proposed algorithm with algorithms are given, and some useful conclusions are drawn.< >

关键词： Neurons Backpropagation algorithms Multi-layer neural network Neural networks Feedforward neural networks Very large scale integration robotics and automation Multilayer perceptrons Numerical simulation Artificial neural networks

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A tactile sensing system for dexterous manipulation

A tactile sensing system for dexterous manipulation

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IEEE International Workshop on Intelligent Robots and Systems (IROS)

作者： B.L. Gery S.N. Gottschlich New York State Center for Advanced Technology in Automation and Robotics and Electrical Computer and Systems Engineering Department Rensselaer Polytechnic Institute Troy NY USA

One factor that limits the range of tasks that robots can perform robustly is the scarcity of useful sensors available to provide feedback to the robot control system. While much progress has been made with vision sensors and force/torque sensors, tactile sensing systems have fallen behind, and so general-purpose tactile sensing systems are not commercially available. The aim of this work is therefore to produce a tactile sensing system that could be manufactured inexpensively, could be used on a wide variety of robotic systems, and would provide the kind of output typically required in dexterous manipulation applications. Such a tactile sensing system will be presented in this paper. The tactile transducers used in this system are based on semiconductive ink technology that allows transducers of any size, shape, and resistance range to be produced merely by altering the ink printing process and substrate geometry. Each sensor outputs three pieces of information that are useful in robotic manipulation-two parameters indicating the location of a contact point on the transducer and one parameter specifying the amount of force being exerted at the contact point. So that the sensing system could support transducers of different shapes and sizes, the analog interface circuitry of this system has been designed to be fully programmable, and also includes circuitry to enable self-calibration with appropriate software.< >

关键词： Transducers Robot sensing systems Sensor systems Tactile sensors Force sensors Ink Shape Circuits Robust control Feedback

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Nonholonomic path planning with inequality constraints

Nonholonomic path planning with inequality constraints

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IEEE International Conference on robotics and automation (ICRA)

作者： A.W. Divelbiss J. Wen New York State Center for Advanced Technology in Robotics and Automation and Department of Electrical Computer and Systems Engineering Rensselaer Polytechnic Institute Troy NY USA

This paper presents an algorithm for finding a kinematically feasible path which satisfies a given set of nonholonomic constraints while enforcing both equality and inequality constraints on the configuration vector. The path planning problem is transformed from a finite time nonlinear control problem into a static root finding problem which is iteratively solved. By using an exterior penalty function method, the constrained root finding problem is converted to an unconstrained problem. Convergence of the algorithm depends upon a certain gradient operator being full rank. It has recently been shown that, in the absence of any configuration inequality constraints, the full rank condition is generic. In this paper, we show the full rank condition for a special inequality constraint case. An experiment in which the algorithm is applied to an actual double tractor-trailer vehicle is presented.< >

关键词： Path planning Control systems Controllability Motion control Velocity control Nonlinear control systems robotics and automation Systems engineering and theory Iterative algorithms Convergence

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Model-based multisensor data fusion: a minimal representation approach

Model-based multisensor data fusion: a minimal representatio...

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IEEE International Conference on robotics and automation (ICRA)

作者： R. Joshi A.C. Sanderson New York State Center for Advanced Technology in Automation and Robotics Electrical Computer and Systems Engineering Department Rensselaer Polytechnic Institute Troy NY USA

A general approach to model-based multisensor data fusion using a minimal representation size criterion is described. Each sensor is modeled by a general constraint equation which defines a data constraint manifold (DCM), and observed sensor data populate the measurement space according to these constraints. The choice of multisensor interpretations is based on a minimal representation size criterion which evaluates the complexity through correspondence and encoded errors weighted by relative sensor accuracy and precision. This general framework automatically selects subsets of data features called constraining data feature sets (CDFS) and chooses the CDFS corresponding to a minimal representation interpretation of the observed data. The resulting procedure fuses heterogeneous sensor readings into a single estimation method. The method is illustrated for a visual and tactile data fusion example. The approach generalizes to problems with non-geometric models, and can be used for multisensor system identification in other domains such as process control.< >

关键词： robotics and automation Sensor fusion Robot sensing systems Sensor systems Probability distribution Data engineering Systems engineering and theory Equations Manifolds Fuses

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Variably-autonomous manipulation

Variably-autonomous manipulation

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IEEE International Conference on robotics and automation (ICRA)

作者： L. Singh A. Silverthorne S. Gottschlich H. Stephanou New York State Center for Advanced Technology in Robotics and Automation Electrical Computer and Systems Engineering Department Rensselaer Polytechnic Institute Troy NY USA

There are numerous applications in which robots are needed to assist rather than replace human operators. These applications typically involve either work in a dangerous environment or performing tasks that are physically impossible for humans to accomplish by themselves. Robots used in this mode do not need to be autonomous because they can essentially be controlled by the operator. Nonetheless, it is difficult for an operator to flawlessly control a robot with a large number of degrees of freedom. Therefore, an intelligent control system is needed to correct and improve the operator's input to the robot. In this paper the authors discuss a central component in this control system known as the variably-autonomous trajectory generator (VATG). The VATG combines input from the operator with input from one or more autonomous control modules (CM) to generate the robot trajectory. The amount of impact the autonomous CMs will have on the overall trajectory will depend on a number of factors such as the task being performed and the sensing modalities available, hence the authors refer to this type of control as being variably-autonomous.< >

关键词： Robot sensing systems robotics and automation Humans Control systems Application software Wrist Tactile sensors Force sensors Grasping Systems engineering and theory

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A fuzzy control system for an automated mining excavator

A fuzzy control system for an automated mining excavator

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IEEE International Conference on robotics and automation (ICRA)

作者： P.J.A. Lever Fei-Yue Wang Deqian Chen Advanced Mining Systems Lab Mining and Geological Engineering Department University of Arizona Tucson Tucson AZ USA Robotics and Automation Lab Systems and Industrial Engineering Department University of Arizona Tucson Tucson AZ USA

To automate a mining excavator the control issues resulting from environmental uncertainties must be solved. In particular the interactions between the excavation tool and the excavation environment are dynamic, unstructured and complex. Thus, generating rigorous mathematical models as required by conventional control techniques is extremely difficult if possible. This paper presents an excavator controller that uses fuzzy logic to interpret forces and torques gathered from a wrist mounted force/torque sensor during the excavation process. This approach enables the transfer of human heuristics and expert knowledge to the controller. Experimental results from several excavation tests using the fuzzy logic controller are given. These results represent the first step toward an integrated approach that uses force/torque, vision, and other sensor data to perform generic tasks in uncertain mining environments.< >

关键词： Fuzzy control Fuzzy logic Force sensors Automatic control Uncertainty Mathematical model Automatic generation control Force control Torque control Wrist

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On-line trajectory planning for autonomous robotic excavation based on force/torque sensor measurements

On-line trajectory planning for autonomous robotic excavatio...

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International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI)

作者： Fei-Yue Wang P.J.A. Lever Robotics and Automation Laboratory Department of Systems and Industrial Engineering University of Arizona Tucson Tucson AZ USA Advanced Mining Systems Laboratory Department of Mining and Geological Engineering University of Arizona Tucson Tucson AZ USA

This paper describes the authors' initial investigation into on-line trajectory planning for autonomous robotic excavation. A dynamic model for arm/environment interaction is proposed. Excavation trajectories are generated using a trapezoidal velocity profile under the maximum force/torque constraints. A scheme for real-time identification of dynamic arm/environment interaction parameters is implemented with a first-order algorithm of Saridis-Stein stochastic approximation. The result of a simulation study is presented to illustrate the proposed trajectory planning approach.< >

关键词： Force measurement Trajectory Robot sensing systems Force sensors Torque measurement robotics and automation Humans Automatic control Fuzzy logic Control systems

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A fuzzy-behavior-based approach for controlling mining excavator bucket/rock interactions

A fuzzy-behavior-based approach for controlling mining excav...

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Conference Record of the IEEE Industry Applications Society Annual Meeting (IAS)

作者： P.J.A. Lever Fei-Yue Wang Xiaobo Shi Deqian Chen Advanced Mining Systems Laboratory Mining and Geological Engineering Department University of Arizona Tucson Tucson AZ USA Robotics and Automation Laboratory Systems and Industrial Engineering Department University of Arizona Tucson Tucson AZ USA

Successful control of an autonomous mining excavator requires sensor feedback from the excavation tool to control unpredictable tool/rock interactions. Conventional control approaches cannot deal effectively with uncertainties in the dynamic and unstructured mining environment. This paper presents a new intelligent control approach that utilizes fuzzy behaviors with fuzzy strategies to control bucket motions for autonomous excavation tasks. In this approach, the control system uses feedback from a bucket mounted force/torque sensor to control excavation motions by sensing and reacting to interactions with rock particles during excavation. A behaviour coordination configuration is developed to improve the controllers effectiveness in reaching its overall excavation goals. It uses fuzzy logic rules to adjust control system output variables and performs goal-driven behaviour selection. This technique is a first step towards realistic control of complex machine/environment interactions in difficult and unpredictable environments, where traditional control approaches are either impossible or computationally excessive. The discussion here focuses on: (a) development of a new control architecture; (b) the individual components of the architecture; and (c) experiments with a simulated excavator using a PUMA 560 robotic arm.< >

关键词： Motion control Control systems Intelligent sensors Fuzzy control Force control Torque control Force feedback Computer architecture Uncertainty Intelligent control

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Resistance of particulate media to excavation: Application to bucket loading

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International Journal of Surface Mining, Reclamation and Environment 1994年第3期8卷 125-129页

作者： Hemami, A. Goulet, S. Aubertin, M. Canadian Centre for Automation and Robotics in Mining Ecole Polytechnique Montreal Quebec Canada Department of Mineral Engineering Ecole Polytechnique Montreal Quebec Canada

In excavation of particulate media the resistive force for cutting through, or digging, must be overcome by the cutting tool. A knowledge about this force is essential for designing the cutting tools and the excavating machinery. Such a knowledge becomes quite important, also, for automating the operation of these machines, which has recently gained a great deal of interest among construction and mining industries. It may be used for feedback purposes in order to monitor and adjust the motion of the excavating tool. In this article the excavation force on a loader bucket during loading is considered. After a preliminary analysis of the various components of this force, its variation in the course of a desired motion of the bucket is determined and is graphically illustrated. © 1994, Taylor & Francis Group, LLC. All rights reserved.

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Computing LQG/H/sub /spl infin// bounded control with guaranteed convergence

Computing LQG/H/sub /spl infin// bounded control with guaran...

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American Control Conference (ACC)

作者： K.M. Black S.Q. Zhu F.L. Lewis Mechanical and Ampace Engineexkg University of Texas Arlington Arlington TX USA Automation d Robotics Research Institute (ARRI) Fort Worth TX USA Moncrief-OE28099Donnell Chair for Autanat ion and Robotics ARRIElectrical Engineering Department University of Texas Arlington Arlington TX USA

A convergence theorem is presented for an algorithm that solves an LQG control problem which includes an H/sub /spl infin// performance bound. The mixed optimization problem setup results in a system of three Riccati equations, two of which are coupled and can not be solved independently. The algorithm rapidly converges to a global minimum under very general assumptions.

关键词： Convergence Hydrogen Optimal control Automatic control Riccati equations Sufficient conditions

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