A characterization of the structure of uncertainty called the generalized matching condition is proposed. The uncertainty is further decomposed into two parts that are 'orthogonal' to each other. On the basis ...
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A characterization of the structure of uncertainty called the generalized matching condition is proposed. The uncertainty is further decomposed into two parts that are 'orthogonal' to each other. On the basis of this decomposition a linear feedback control design is proposed for linear uncertain systems. The control always exists if the generalized matching condition is met. The design is illustrated by a practical example.< >
A model-based vision system requires models in order to predict object appearances. How an object appears in the image is the result of interaction between the object properties and the sensor characteristics. Thus in...
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This paper presents a model-based object recognition method which combines a bottom-up evidence accumulation process and a top-down hypothesis verification process. The hypothesize-and-test paradigm is fundamental in ...
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An algorithm to assemble large jigsaw puzzles using curve matching and combinatorial optimization techniques is presented. The pieces are photographed one by one and then the assembly algorithm, which uses only the pu...
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This paper presents two new formal frameworks for learning. The first framework requires the learner to approximate an unknown function, given examples for the function as well as some background information on it. As...
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The authors use occupancy grids to combine range information from sonar and one-dimensional stereo into a two-dimensional map of the vicinity of a robot. Each cell in the map contains a probabilistic estimate of wheth...
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The authors use occupancy grids to combine range information from sonar and one-dimensional stereo into a two-dimensional map of the vicinity of a robot. Each cell in the map contains a probabilistic estimate of whether it is empty or occupied by an object in the environment. These estimates are obtained from sensor models that describe the uncertainty in the range data. A Bayesian estimation scheme is applied to update the current map using successive range readings from each sensor. The occupancy grid representation is simple to manipulate, treats different sensors uniformly, and models uncertainty in the sensor data and in the robot position. It also provides a basis for motion planning and creation of more abstract object descriptions.< >
The problem of a thin rigid rod sliding on a horizontal surface in the plane is considered. This problem is commonly cited as an example of the inconsistency of planar rigid-body Newtonian mechanics. The existence of ...
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The problem of a thin rigid rod sliding on a horizontal surface in the plane is considered. This problem is commonly cited as an example of the inconsistency of planar rigid-body Newtonian mechanics. The existence of a consistent solution, using Routh's analysis of rigid-body impact is demonstrated.< >
As various dextrous robot hands are designed and built, a major question is how to develop device-independent robot hand controllers. This would allow the low-level control problems to be separated from high level fun...
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As various dextrous robot hands are designed and built, a major question is how to develop device-independent robot hand controllers. This would allow the low-level control problems to be separated from high level functionality. GeSAM is a generic robot hand controller that is based on a model of human prehensile function. It focuses on the relationship between geometric object primitives and the ways a hand can perform prehensile behaviors. The authors show how the relationship between object primitives and a useful set of grasp modes can be learned by an adaptive neural network. By adding training points as necessary, system performance can be improved, avoiding the tedious job of computing every relationship by hand.< >
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