We present an integrated methodology that can be used to extract the depth from a sequence of images. The method combines the ability of stereo processing to acquire highly accurate depth measurements and the efficien...
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We present an integrated methodology that can be used to extract the depth from a sequence of images. The method combines the ability of stereo processing to acquire highly accurate depth measurements and the efficiency of spatial and temporal gradient analysis. As a result of this integration, depth measurements of a high quality are obtained at a speed approximately ten-times higher than that of stereo processing. Without any a priori information of the locations of the points in the scene, the correspondence problem in stereo processing is computationally expensive. In our approach, we use the spatial and temporal gradient analysis, which has been shown to provide the depth with a high efficiency but limited accuracy, to guide the stereo matching process. Experiments for lateral and axial camera translations have acquired depth results with a mean error of less than 3 percent.
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 NN as a compensator for the complex problem of Cartesian space control. In particular we examine the differences in system performance when the same NN compensator is applied at different locations in the controller. 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 joint torque/force. To facilitate the analysis, a new NN training signal is introduced. The study is extended to non-model based Cartesian control problem. Simulation results are also presented.
Performance of impedance controller for robot force tracking is affected by the uncertainties in the robot model and environment stiffness. The purpose of the paper is to improve the controller robustness by applying ...
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Performance of impedance controller for robot force tracking is affected by the uncertainties in the robot model and environment stiffness. The purpose of the paper is to improve the controller robustness by applying the neural network technique to compensate for the uncertainties in the robot model. A novel error signal is proposed for the neural network training. In addition, an algorithm is developed to determine the reference trajectory when the environment stiffness is unknown. Simulations show that highly robust position/force tracking by a three degrees-of-freedom robot can be achieved under large uncertainties.
This paper highlights a ranging sensor that can be calibrated at standoffs of 1 to 3 feet with a depth of field of /spl ap/1 ft. Tests at a 16" standoff have produced a 0.004 inch standard deviation in height mea...
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This paper highlights a ranging sensor that can be calibrated at standoffs of 1 to 3 feet with a depth of field of /spl ap/1 ft. Tests at a 16" standoff have produced a 0.004 inch standard deviation in height measurement errors. The data density and field of view are programmable. The sensor is positioned robotically, allowing it to provide accurate, shed-range measurements prior to manipulation tasks. The sensor head is relatively inexpensive (/spl ap/$10 k) and is designed for in situ calibration. This approach is intended to allow replacement components to be installed, calibrated, and validated without decontamination. Calibration, validation and data acquisition are all designed to be performed remotely and in a highly automated fashion. These in situ features of the design are targeted for the interest of industry with the aim of producing a sensor having a longer lifetime and a lower maintenance cost.
The image understanding work we present is part of a navigation support system. We explore the use of fuzzy techniques for image understanding via perceptual organization. A brief review of previous work on perceptual...
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The image understanding work we present is part of a navigation support system. We explore the use of fuzzy techniques for image understanding via perceptual organization. A brief review of previous work on perceptual organization introduces our motivation for using fuzzy techniques for representation which in turns entails their use for reasoning about the result of the organization. The approach is supported by experimental results obtained for an office scene environment.< >
A real-time correspondence based tracking algorithm is detailed. The system uses a pipeline processor, a general purpose processor, a camera and a display. The minimum noise and correlation energy (MINACE) filter is u...
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A real-time correspondence based tracking algorithm is detailed. The system uses a pipeline processor, a general purpose processor, a camera and a display. The minimum noise and correlation energy (MINACE) filter is used in the tracking algorithm as it provides a good combination of speed, accuracy and flexibility for the targeted hardware system. The system designed is fast and tracking is accomplished at a rate of 15 Hz. The system is adaptive and does not rely on a previous model of the object; the training image for filter synthesis is acquired from previous image frames and the filter is synthesized online to accommodate 3D variations of the target being tracked. The system tracks an object consistently as is demonstrated by the low deviation of the results in the evaluation.
Tracing leaks of airborne radioactive, poisonous or flammable materials is a potentially dangerous activity that could be undertaken by robotic systems. This paper describes a practical investigation of the possibilit...
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Tracing leaks of airborne radioactive, poisonous or flammable materials is a potentially dangerous activity that could be undertaken by robotic systems. This paper describes a practical investigation of the possibility of developing simple, low cost, autonomous robots to perform this task. It is envisaged that these robots would be used in large numbers. This would improve reliability through redundancy and provide large area coverage from a wide distribution of robots. Failure of a single unit would not jeopardise the overall sensing operation. Sensing and control techniques developed to perform leak location in a simplified laboratory environment are described and experimental results are presented.
We compare two classes of algorithms for estimating subpixel, rigid-body translation between two images. One class is based on optical flow. Optical flow algorithms determine translations between images from estimates...
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We compare two classes of algorithms for estimating subpixel, rigid-body translation between two images. One class is based on optical flow. Optical flow algorithms determine translations between images from estimates of spatial and temporal derivatives of brightness. The other class is based on block matching. Block matching algorithms determine translations between images by minimizing the difference between shifted (warped) versions of the original images. We show that these two classes of algorithms are equivalent for subpixel displacements. Specifically, we show that all block matching algorithms that use bilinear interpolation can be recast into equivalent optical flow formulations, and that all algorithms based on optical flow using first-order derivative estimators can be recast into equivalent block matching formulations.
Most simulation and animation systems utilized in robotics are concerned with simulation of the robot and its environment without simulation of sensors. These systems have difficulty in handling robots that utilize se...
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Most simulation and animation systems utilized in robotics are concerned with simulation of the robot and its environment without simulation of sensors. These systems have difficulty in handling robots that utilize sensory feedback in their operation. In this paper, a new design of an environment for simulation, animation, and visualization of sensor-driven robots is presented. As sensor technology advances, increasing numbers of robots are equipped with various types of sophisticated sensors. The main goal of creating the visualization environment is to aid the automatic robot programming and off-line programming capabilities of sensor-driven robots. The software system will help the users visualize the motion and reaction of the sensor-driven robot under their control program. Therefore, the efficiency of the software development is increased, the reliability of the software and the operation safety of the robot are ensured, and the cost of new software development is reduced. Conventional computer-graphics-based robot simulation and animation software packages lack of capabilities for robot sensing simulation. This paper describes a system designed to overcome this deficiency.
In order to solve the speed problem and shallow reasoning problem met in current research in fault diagnosis expert system, this paper presents a model based parallel fault diagnosis expert system for energy managemen...
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