Random Finite Sets For Robot Mapping Slam


Download Random Finite Sets For Robot Mapping Slam PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Random Finite Sets For Robot Mapping Slam book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages.

Download

Random Finite Sets for Robot Mapping & SLAM


Random Finite Sets for Robot Mapping & SLAM

Author: John Stephen Mullane

language: en

Publisher: Springer

Release Date: 2011-05-19


DOWNLOAD





The monograph written by John Mullane, Ba-Ngu Vo, Martin Adams and Ba-Tuong Vo is devoted to the field of autonomous robot systems, which have been receiving a great deal of attention by the research community in the latest few years. The contents are focused on the problem of representing the environment and its uncertainty in terms of feature based maps. Random Finite Sets are adopted as the fundamental tool to represent a map, and a general framework is proposed for feature management, data association and state estimation. The approaches are tested in a number of experiments on both ground based and marine based facilities.

Robotic Navigation and Mapping with Radar


Robotic Navigation and Mapping with Radar

Author: Martin Adams

language: en

Publisher: Artech House

Release Date: 2012


DOWNLOAD





A practical treatment of short-range radar processing for reliable object detection at ground level.

Advances in Swarm Intelligence, Part II


Advances in Swarm Intelligence, Part II

Author: Ying Tan

language: en

Publisher: Springer Science & Business Media

Release Date: 2011-05-26


DOWNLOAD





The two-volume set (LNCS 6728 and 6729) constitutes the refereed proceedings of the International Conference on Swarm Intelligence, ICSI 2011, held in Chongqing, China, in June 2011. The 143 revised full papers presented were carefully reviewed and selected from 298 submissions. The papers are organized in topical sections on theoretical analysis of swarm intelligence algorithms, particle swarm optimization, applications of pso algorithms, ant colony optimization algorithms, bee colony algorithms, novel swarm-based optimization algorithms, artificial immune system, differential evolution, neural networks, genetic algorithms, evolutionary computation, fuzzy methods, and hybrid algorithms - for part I. Topics addressed in part II are such as multi-objective optimization algorithms, multi-robot, swarm-robot, and multi-agent systems, data mining methods, machine learning methods, feature selection algorithms, pattern recognition methods, intelligent control, other optimization algorithms and applications, data fusion and swarm intelligence, as well as fish school search - foundations and applications.