Occupancy grids are a probabilistic method for fusing multiple sensor readings into surface maps of the environment. Although the underlying theory has been understood for many years, the intricacies of applying it to realtime sensor interpretation have been neglected. This paper analyzes how refined sensor models (including specularity models) and assumptions about independence are crucial iss...

This paper presents the use of auditory occupancy grids (AOGs) for mapping of a mobile robot’s acoustic environment. An AOG is a probabilistic map of sound source locations built from multiple measurements using techniques from both probabilistic robotics and sound localization. The mapping is simulated, tested for robustness, and then successfully implemented on a threemicrophone mobile robot ...

In recent years, techniques for building metric maps of indoor environments have been intensely studied, and they perform very well in noumerous applications. Simultaneous Localization and Mapping (SLAM) methods produce globally consistent, metric maps of the explored environment. Although such maps describe how the environment looks like and can be used for navigation, there exist no abstracte...

This paper presents a new way to acquire occupancy grid maps with mobile robots. Virtually all existing occupancy grid mapping algorithms decompose the highdimensional mapping problem into a collection of onedimensional problems, where the occupancy of each grid cell is estimated independently of others. This induces conflicts that can lead to inconsistent maps. This paper shows how to solve th...

This article describes a new algorithm for acquiring occupancy grid maps with mobile robots. Virtually all existing occupancy grid mapping algorithms decompose the highdimensional mapping problem into a collection of one-dimensional problems, where the occupancy of each grid cell is estimated independently. This induces conflicts that may lead to inconsistent maps. This article shows how to sol...

—Reliable estimates of population parameters derived from survey methods are essential for decision making in management of endangered species. We evaluated whether point-count surveys used in conjunction with occupancy and binomial mixture models (BMMs) constituted a reliable approach for monitoring the federally endangered Golden-cheeked Warbler (Setophaga chrysoparia) on a preserve in centra...

Probabilistic occupancy grids are a common and well-proven spatial representation used in robot mapping. However, representing very large environments with high resolution can still impose prohibitive memory requirements. A quadtree is a well-known data structure able to achieve compact representations of large two-dimensional binary arrays. We extend this idea and present probabilistic quadtre...

Occupancy Grids have been used to represent the environment for some time. More recently, the Bayesian Occupancy Filter (BOF), which provides both an estimate of likelihood of occupancy of each cell, AND a probabilistic estimate of the velocity of each cell in the grid, has been introduced and patented. This work presents the first experiments in the use of the BOF to fuse data obtained from st...

Development of various robotic algorithms can be supported with the aid of robot simulation programs. We present the Webots mobile robot simulator and its applicability to handle machine-learning methods. Furthermore, we show advantages and disadvantages of different navigation paradigms. We focus our investigation on metric navigation and especially on the creation and the usage of occupancy g...