Three-dimensional (3D) building model is one of the most important components in a cyber city implementation and application. This study developed an effective and highly automated system to generate and map (near) photo-realistic texture attributes onto 3D building models using digital video sequences. The system extracted frames with overlapped textures of building facades and integrated them...

This communication addresses the issue of concurrent map building and localization (CML) for a mobile robot in an unknown environment. The proposed solution extends over previous contributions in that the environment must not be static, nor the landmarks be uniquely identifiable. To this aim we introduce a map model that includes not only the robot and landmark locations in a reference frame, b...

Nearest Neighbor Search plays a vital role in building road-maps in Motion Planning. These are implemented in any Road-map building method such as PRM, OBPRM, Gauss PRM, etc. Motion Planning is the science of designing a successfully implementable plan in any Configuration Space (often called C-space) in order to move the Robot from a given Start Configuration to a Goal Configuration by avoidin...

The present study aimed to test the function of the exocentric view on the acquisition of survey knowledge during spatial navigation in a virtual multilevel building. Subjects navigated a virtual three-level building in three conditions. In the first condition, subjects navigated the building without any aid. In the second condition, subjects navigated the building with the aid of a three-dimen...

We implement a light-weighted and fast approach, SmartGuide, to localize and recognise a distant unknown building, using only one photo of a target building and a local 2D Google map without other prior knowledge. SmartGuide first extracts the top view contours of a building from its sideview photo, by applying vanishing point and Manhattan World Assumption. It then fetches a candidate building...

This paper describes a mobile robot equipped with a sonar sensor array, Werrimbi, in a guided feature based map building task in an indoor environment. Common indoor landmarks such as planes, corners and edges are located and classified with a multiple transducer sensor array. Accurate odometry information is derived from a pair of narrow unloaded encoder wheels. Discrete sonar observations are...

A feature based approach to simultaneous localization and map building (SLAM) is to use the information obtained by sensors mounted on a vehicle to build and update a map of the environment and compute the vehicle location in that map. One of the critical problems in obtaining a robust SLAM solution is data association, i.e. relating sensor measurements to features in the map that has been buil...

When service robots carry on mission planning and execution, they not only need structural information about the environment to navigation and localization, but also need to possess deeper knowledge to endow a robot with higher degrees of autonomy and intelligence. However it is hard for a robot to cognize the semantic description such as the function attributes of objects and rooms only relyin...

The full covariance solution to simultaneous localization and map building based on extended Kalman filter requires update time quadratic in the number of landmarks in the map. In order to improve the computational efficiency, this paper reorganizes system state vector and system models. The state of mobile robot is redefined and represented indirectly. The higher dimensional system models and ...

This paper deals with the fusion of random variables when cross covariances are unknown. This is a vital problem in nearly every real world application since cross covariances are often impossible to obtain but also cannot be ignored. We provide a rigorous derivation of the fusion equations which are also known as covariance intersection. This approach allows us to derive an iterative scheme fo...