Robust estimators have become popular tools for solving a wide range of problems in computer vision. Despite many successes in this field, there is still a need for estimators, which are suited to specific problems su...
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This paper considers the problem of finding a robust solution to the optic flow problem. The optical flow field is recovered by solving a system of over-determined linear equations with all the data matrices containin...
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The project described in this paper investigates the idea that, in some circumstances, the functions of a complex mechanism can be performed by a large number of simpler units. There are example in nature that support...
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In this paper we compare the performance of a dead-reckoning system for robot navigation to a system using an Extended Kalman Filter (EKF). Dead-reckoning systems are able to approximate position and orientation by fe...
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ISBN:
(纸本)0819426415
In this paper we compare the performance of a dead-reckoning system for robot navigation to a system using an Extended Kalman Filter (EKF). Dead-reckoning systems are able to approximate position and orientation by feeding data (provided usually by local sensors) to the kinematic model of the vehicle. These systems are subject to many different sources of error. EKFs have the ability to combine the same information and compensate for most of these errors to yield a better estimate. Our simulation results using a simplified kinematic model of Rocky 7 (an experimental rover used in the Mars exploration program at Jet Propulsion laboratory (JPL)) show that an improvement in performance up to 40% (position error) can be achieved. The local sensors used are: wheel encoders, steering angle potentiometer and gyroscope. Involvement of global sensor measurements can drastically increase the accuracy of the estimate. The lack of GPS or magnetic field on Mars narrows our choices for global localization. Landmarks, such as the sun can be used as natural beacons (reference point for absolute measurements). A sun sensor (SS) that measures the absolute orientation of the rover has been built by Lockheed Martin and now is part of the sensor suite of Rocky 7. The SS measurement is crucial for the estimation filter and we show that the accuracy of the estimation decreases exponentially as the frequency of the SS data fed to the EKF decreases.
作者：
Jung, SHsia, TCRobotics Research Laboratory
Department of Electrical and Computer Engineering University of California Davis CA 95616 USA. E-mail: hsia@ece.ucdavis.edu and jung@ece.ucdavis.edu
It is well known that computed torque robot control is subjected to performance degradation due to uncertainties in robot model, and application of neural network (NN) compensation techniques are promising. In this pa...
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It is well known that computed torque robot control is subjected to performance degradation due to uncertainties in robot model, and application of neural network (NN) compensation techniques are promising. In this paper we examine the effectiveness of neural network (NN) as a compensator for the complex problem of Cartesian space control. In particular we examine the differences in system performance of accurate position control when the same NN compensator is applied at different locations in the controller structure. It is found that using NN to modify the reference trajectory to compensate for model uncertainties is much more effective than the traditional approach of modifying control input or joint torque/force. To facilitate the analysis, new NN training signal is introduced and used for all cases. The study is also extended to non-model based Cartesian control problems. Simulation results with three-link rotary robot are presented and performances of different compensating locations are compared.
In this paper, we derive tracking control laws for non-minimum phase nonlinear systems with both fast and slow, possibly unstable, zero dynamics. The fast zero dynamics arise from a perturbation of a nominal system. T...
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In this paper, we derive tracking control laws for non-minimum phase nonlinear systems with both fast and slow, possibly unstable, zero dynamics. The fast zero dynamics arise from a perturbation of a nominal system. These fast zeros can be problematic in that they may be in the right half plane and may cause large magnitude tracking control inputs. In this paper, we combine the ideas from some recent work of Hunt, Meyer and Su with that of Devasia, Chen and Paden on an asymptotic tracking procedure for non-minimum phase nonlinear systems. We give (somewhat subtle) conditions under which the tracking control input is bounded as the magnitude of the perturbation of the nominal system becomes zero. Explicit bounds on the control inputs are calculated for both SISO and MIMO systems using some interesting non-standard singular perturbation techniques. The method is applied to a suite of examples, including the simplified planar dynamics of VTOL and CTOL aircraft.
The manufacturing of complex products often involves the assembly of other products, or sub-assemblies. Furthermore, these sub-assemblies may be manufactured by different suppliers. As a result, the specification of t...
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This paper deals with the regulation of the thermal characteristics of Gas Metal Arc (GMA) welding. A previously developed model is used for the open loop predictions. At the first level of the hierarchy, a parameteri...
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This paper deals with the regulation of the thermal characteristics of Gas Metal Arc (GMA) welding. A previously developed model is used for the open loop predictions. At the first level of the hierarchy, a parameterized Generalized Predictive Control (GPC) algorithm is selected among other control techniques, due to its robustness against modeling errors and parameter variations. A coordinator, at the second level of the hierarchy, specifies a set of reliable values for the parameters of GPC, so that stability is assured. A representative set of simulation results is included, along an evaluation of the advantages and limitations of the proposed hierarchical GPC technique.
In this paper the control problem of telemanipulators is considered under the condition that they are subject to modeling and other uncertainties of considerable levels. The design is based on the S. Lee and H. S. Lee...
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ISBN:
(纸本)0780341236
In this paper the control problem of telemanipulators is considered under the condition that they are subject to modeling and other uncertainties of considerable levels. The design is based on the S. Lee and H. S. Lee teleoperator control scheme, which is modified so as to be able to compensate the uncertainties, and is implemented using a partitioned multilayer perceptron neural network. Several subnetworks are used each one identifying a term of the manipulator's dynamic model. A new learning algorithm is proposed which distributes the learning error to each subnetwork and enables online training Several simulation results are provided which show the robustness ability by the partitioned neurocontroller, and compare it with the results obtained through sliding mode control.
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