technology, equipment and applications related to the automated assembly and robotics industries. Feature articles include updates on the latest manufacturing research, tutorials on a particular manufacturing technology and field reports on installed manufacturing technologies, all from a technical perspective. Each issue also includes additional brief articles, product announcements and event ...

Stochastic mapping is an approach to the concurrent mapping and localization (CML) problem. The approach is powerful because feature and robot states are explicitly correlated. Improving the estimate of any state automatically improves the estimates of correlated states. This paper describes a number of extensions to the stochastic mapping framework, which are made possible by the incorporation...

Probabilistic robotics, most often applied to the problem of simultaneous localisation and mapping (SLAM), requires measures of uncertainty to accompany observations of the environment. This paper describes how uncertainty can be characterised for a vision system that locates coloured landmarks in a typical laboratory environment. The paper describes a model of the uncertainty in segmentation, ...

This article presents SLAM, an Automatic Solver for Lexical Metaphors like “déshabiller* une pomme” (to undress* an apple). SLAM calculates a conventional solution for these productions. To carry on it, SLAM has to intersect the paradigmatic axis of the metaphorical verb “déshabiller*”, where “peler” (“to peel”) comes closer, with a syntagmatic axis that comes from a corpus where “peler une pom...

Many progresses have been made on SLAM so far, and various visual SLAM approaches have proven their effectiveness in realistic scenarios. However, there are many other improvements that can be made to SLAM thanks to vision, essentially for the mapping and data association functionalities. This paper sketches some of these improvements, on the basis of recent work in the literature and of on-goi...

This article presents an approach to SLAM that takes advantage of panoramic images. Landmarks are interest points detected and matched in the images and mapped according to a bearings-only SLAM approach. As they are acquired and processed, the panoramic images are also indexed and stored into a database. A database query procedure, independent of the robot and landmark position estimates, is ab...

ions. Following SLAM, abstractions are represented by Boolean Programs. Unlike SLAM, the semantics of these programs is given via a variant of Mixed Transition Systems (MixTS) [7, 11]. Compared to Modal and 3-valued TSs, MixTSs allow for (a) 1: 2: 3: 4: 5: 6: 7: 8: 9: 10: 11: 12: 13: 14: 15: 16: 17: int p1,p2,p3,x,y; p1=p2=p3=x=y=5; if(p3<=0) return; if(y<0) {if(x>2){ if(y>10) {if(p2>0) ERROR;}...

Observability is a key aspect of the state estimation problem of SLAM, However, the dimension and variables of SLAM system might be changed with new features, to which little attention is paid in the previous work. In this paper, a unified approach of observability analysis for SLAM system is provided, whether the dimension and variables of SLAM system are changed or not, we can use this approa...

We present an algorithm that can segment and track partial planar templates, from a sequence of images taken from a moving camera. By “partial planar template”, we mean that the template is the projection of a surface patch that is only partially planar; some of the points may correspond to other surfaces. The algorithm segments each image template to identify the pixels that belong to the domi...