In this paper we present a fast motion detection technique based on laser data and odometry/imu information. This technique instead of performing a complete SLAM (Simultaneous Localization and Mapping) solution, is based on transferring occupancy information between two consecutive data grids. We plan to use the output of this work for Bayesian Occupancy Filter (BOF) framework to reduce process...

We present a mapping approach to scene understanding based on active stereo vision. We generalise traditional static multi-camera rectification techniques to enable active epipolar rectification and intuitive representation of the results. The approach is shown to enable the use of any static stereo algorithms with active multi-camera systems. In particular, we show the use of the framework to ...

Abstract Trees play an important role in the complex system of urban environments. Their benefits to environment and health are manifold. Yet, especially near streets, traffic can be impaired by a limited clearance. Even injuries could caused breaking tree parts. Hence, it is capture trees frame cadastre ensure regular monitoring. Mobile laser scanning (MLS) used for data acquisition, followed ...

This paper describes new method for building occupancy grid from single camera, automatic calibration of this method and approach how to use this internal representation for cleaning unknown environment. The algorithm is designed for indoor application. This assumption is used for calculating inverse perspective transformation of the gathered image. The paper brings an overview of path-planning...

In this paper we deene the task of place learning and describe one approach to this problem. The framework represents distinct places using evidence grids, a probabilistic description of occupancy. Place recognition relies on case-based classiication, augmented by a registration process to correct for translations. The learning mechanism is also similar to that in case-based systems, involving ...

In this paper we deene the task of place learning and describe one approach to this problem. The framework represents distinct places using evidence grids, a probabilistic description of occupancy. Place recognition relies on case-based classiication, augmented by a registration process to correct for translations. The learning mechanism is also similar to that in case-based systems, involving ...

This article proposes a perception scheme in the field of intelligent vehicles. The method exploits prior map knowledge and makes use of evidential grids constructed from the sensor data. Evidential grids are based on occupancy grids and the formalism of the Dempster–Shafer theory. Prior knowledge is obtained from a geographic map which is considered as an additional source of information and c...

In this paper we provide an overview of a new framework for robot perception, real-world modelling, and navigation that uses a stochastic tesselated representation of spatial in­ formation called the Occupancy Grid. The Occupancy Grid is a multi-dimensional randomfield model that maintains probabilistic estimates of the occupancy state of each cell in a spatia/lattice. Bayesian estimation mecha...

This paper addresses the problem of perception and localisation for a mobile robot in an unknown environment. It describes a modelling of the environment based on two certainty grids: one local model and the other one a global model. Localisation of the robot is reduced to nding the best alignment of the local certainty grid onto the global certainty grid. Four localisation procedures to correc...