The ability of achieving a semantic understanding of workspaces is an important capability for mobile robot.A method is proposed to categorize different places in a typical indoor environment by using a Kinect sensors...The ability of achieving a semantic understanding of workspaces is an important capability for mobile robot.A method is proposed to categorize different places in a typical indoor environment by using a Kinect sensors for mobile robot exploration.At first,the invariant feature based images stitching approach is adopted to form a panoramic image according to Kinect visual information,and the translation between Kinect depth information and obstacle distance information is performed to obtain virtual LIDAR data.Then,the semantic classifier is designed by using convolutional neural networks(CNN)for indoor place eategorization based on Kinect visual observations with panoramic view.At last,a frontier-based exploration method is applied to carry out indoor autonomous exploration of mo-bile robots,which integrates the CNN-based categorization approach.The proposed method has been implemented and tested on a real robot,and experiment results demonstrate the approach effective-ness on solving the semantic categorization problem for mobile robot exploration.展开更多
The paper discusses semalltics of encodings in logical frameworkswhere equalities in object calculi are represented by families of types as the case inELF. The notion of Leibniz equality in a category is introduced. T...The paper discusses semalltics of encodings in logical frameworkswhere equalities in object calculi are represented by families of types as the case inELF. The notion of Leibniz equality in a category is introduced. Two morphisms ina category are Leibniz equal if they are seen so by an internal category. The usualcategorical properties are then relativized to r-properties by requiring mediatingmorphisms to be unique up to some Leibniz equality. Using these terminologies,it is shown, by an example, that the term model of the encoding of an adequatelyrepresented object calculus is r-isomorphic to the term model of the object language.展开更多
基金Supported by the National Key Basic Research Program of China(No.2013CB035503)
文摘The ability of achieving a semantic understanding of workspaces is an important capability for mobile robot.A method is proposed to categorize different places in a typical indoor environment by using a Kinect sensors for mobile robot exploration.At first,the invariant feature based images stitching approach is adopted to form a panoramic image according to Kinect visual information,and the translation between Kinect depth information and obstacle distance information is performed to obtain virtual LIDAR data.Then,the semantic classifier is designed by using convolutional neural networks(CNN)for indoor place eategorization based on Kinect visual observations with panoramic view.At last,a frontier-based exploration method is applied to carry out indoor autonomous exploration of mo-bile robots,which integrates the CNN-based categorization approach.The proposed method has been implemented and tested on a real robot,and experiment results demonstrate the approach effective-ness on solving the semantic categorization problem for mobile robot exploration.
文摘The paper discusses semalltics of encodings in logical frameworkswhere equalities in object calculi are represented by families of types as the case inELF. The notion of Leibniz equality in a category is introduced. Two morphisms ina category are Leibniz equal if they are seen so by an internal category. The usualcategorical properties are then relativized to r-properties by requiring mediatingmorphisms to be unique up to some Leibniz equality. Using these terminologies,it is shown, by an example, that the term model of the encoding of an adequatelyrepresented object calculus is r-isomorphic to the term model of the object language.
