Mapping environments is a fundamental task for a rescue robot. In this paper we present techniques that we have developed for mapping rescue environments within the SPQR-Rescue team participating in the RoboCup 2004 Real Rescue competition. After an analysis of existing techniques for simultaneous localization and mapping (SLAM) we have devised a method suitable for planar environment (i.e. yel...

Recall that the main difficulty with particle filtering is that with a high dimensional state variable xt, an impossibly large number of particles is needed to accurately represent P (xt|z0:t). In some filtering problems, it is possible to exploit conditional independence of components of the state variables x1:t in order to reduce the number of particles needed. In this lecture we will see exa...

We present three functional interpretations of intuitionistic linear logic and show how these correspond to well-known functional interpretations of intuitionistic logic via embeddings of IL into ILL. The main difference from previous work of the second author is that in intuitionistic linear logic the interpretations of !A are simpler (at the cost of an asymmetric interpretation of pure ILL) a...

This paper presents a method for fast calculation of the egomotion done by a robot using visual features. The method is part of a complete system for automatic map building and Simultaneous Location and Mapping (SLAM). The method uses optical flow in order to determine if the robot has done a movement. If so, some visual features which do not accomplish several criteria are deleted, and then th...

This paper presents a robust multi-loop airborne SLAM structure which augments wind information into the state of 6DoF Simultaneous Localisation and Mapping (SLAM). The relative air velocity observation from an air data system can be used to estimate the error of the vehicle state. However due to a priori unknown wind information, it cannot directly be used for that purpose. This can be tackled...

This paper reports on an integrated navigation algorithm for the visual simultaneous localization and mapping (SLAM) robotic area coverage problem. In the robotic area coverage problem, the goal is to explore and map a given target area within a reasonable amount of time. This goal necessitates the use of minimally redundant overlap trajectories for coverage efficiency; however, visual SLAM’s n...

Block copolymers are fascinating and complex materials that have been used in a range of diverse scientific and technological capacities. We demonstrate that a single one-step approach based on dual simultaneous polymerizations is a viable technique for the synthesis of a wide range of block copolymers by combining two dissimilar polymerization systems and using a dual-functional initiator. The...

We propose an efficient and scalable method for incrementally building a dense, semantically annotated 3D map in real-time. The proposed method assigns class probabilities to each region, not each element (e.g., surfel and voxel), of the 3D map which is built up through a robust SLAM framework and incrementally segmented with a geometric-based segmentation method. Differently from all other app...

This paper presents a novel method of combining topological and feature-based mapping strategies to create a hierarchical approach to simultaneous localization and mapping (SLAM). More than simply running both processes in parallel, we use the topological mapping procedure to organize local feature-based methods. The result is an autonomous exploration and mapping strategy that scales well to l...

While many visual simultaneous localisation and mapping (SLAM) systems use point features as landmarks, few take advantage of the edge information in images. Those SLAM systems that do observe edge features do not consider edges with all degrees of freedom. Edges are difficult to use in vision SLAM because of selection, observation, initialisation and data association challenges. However, a map...