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Robotic Mapping and Exploration_Springer Tracts in Advanced Robotics Volume 55


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Authors(Editors):

        Cyrill Stachniss

Publisher: Springer

Pub Date: 2009

Pages: 203

ISBN 978-3-642-01096-5

e-ISBN 978-3-642-01097-2

DOI 10.1007/978-3-642-01097-2



Foreword

Simultaneous localization and mapping is a highly important and active area

in mobile robotics. The ability to autonomously build maps is widely regarded

as one of the fundamental preconditions for truly autonomous mobile

robots. In the past, the SLAM has mostly been addressed as a state estimation

problem and the incorporation of control into the map learning and

localization process is a highly interesting research question. In this book by

Cyrill Stachniss, the reader will find interesting and innovative solutions to

the problem of incorporating control into the SLAM problem. I know Cyrill

since over eight years and I still appreciate his enthusiasm in developing new

ideas and getting things done. He has been working with a large number

of different robots, participating in several public demonstrations, and has

gained a lot of experience which can also be seen from his large number of

papers presented at all major robotic conferences and in journals. His work

covers a variety of different topics. He has acquired several project grants and

received several awards. He furthermore is an associate editor of the IEEE

Transactions on Robotics. It’s safe to say that he is an expert in his field.

This book is a comprehensive introduction to state-of-the-art technology in

robotic exploration and map building. The reader will find a series of solutions

to challenging problems robots are faced with in the real world when they

need to acquire a model of their surroundings. The book focuses on autonomy

and thus the robot is not supposed to be joysticked though the world but

should be able to decide about his actions on its own. I regard the ability

to learn maps by making own decisions as a key competence for autonomous

robots. Cyrill rigorously applies probabilistic and decision-theoretic concepts

to systematically reducing the uncertainty in the belief of a robot about its

environment and its pose in the environment.

The book contains impressively demonstrates the capabilities of the described

solutions by showing results obtained from real robotic datasets.

A further strength lies in the sound and thorough evaluation of all presented

techniques going beyond the world of simulation. At this point, I

would like to encourage the reader to follow Cyrill’s example to take real

robots and data obtained with real robots to demonstrate that novel approaches

work in reality. For readers not in possession of particular sensors

or for comparison purposes, Cyrill and colleagues have created a Web site

(
http://www.openslam.org/)
in which the community can share implementations

of SLAM approaches and where the reader will find links to datasets

to support future research.

Freiburg, Germany

February 2009

Wolfram Burgard







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Robotic Mapping and Exploration_Springer Tracts in Advanced Robotics Volume 55.Cyrill Stachniss.Springer.2009



Robotic Mapping and Exploration_Springer Tracts in Advanced Robotics Volume 55.Cyrill Stachniss.Springer.2009



Robotic Mapping and Exploration_Springer Tracts in Advanced Robotics Volume 55.Cyrill Stachniss.Springer.2009



Robotic Mapping and Exploration_Springer Tracts in Advanced Robotics Volume 55.Cyrill Stachniss.Springer.2009



Robotic Mapping and Exploration_Springer Tracts in Advanced Robotics Volume 55.Cyrill Stachniss.Springer.2009



Robotic Mapping and Exploration_Springer Tracts in Advanced Robotics Volume 55.Cyrill Stachniss.Springer.2009



Robotic Mapping and Exploration_Springer Tracts in Advanced Robotics Volume 55.Cyrill Stachniss.Springer.2009


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