© 2013

Semantic 3D Object Maps for Everyday Robot Manipulation

  • Recent research on Semantic 3D Object Models as a novel representation of the robot’s operating environment

  • Applies Semantic 3D Object Mapping to Everyday Manipulation in Human Living Environments

  • Displays how these models can be automatically acquired from dense 3D range data


Part of the Springer Tracts in Advanced Robotics book series (STAR, volume 85)

Table of contents

  1. Front Matter
    Pages 1-19
  2. Radu Bogdan Rusu
    Pages 1-11
  3. Semantic 3D Object Mapping Kernel 15

    1. Front Matter
      Pages 13-13
    2. Radu Bogdan Rusu
      Pages 15-25
    3. Radu Bogdan Rusu
      Pages 27-31
    4. Radu Bogdan Rusu
      Pages 33-60
    5. Radu Bogdan Rusu
      Pages 61-74
    6. Radu Bogdan Rusu
      Pages 75-85
  4. Mapping of Indoor Environments

    1. Front Matter
      Pages 87-87
    2. Radu Bogdan Rusu
      Pages 89-108
    3. Radu Bogdan Rusu
      Pages 109-136
    4. Radu Bogdan Rusu
      Pages 137-146
  5. Applications

    1. Front Matter
      Pages 147-147
    2. Radu Bogdan Rusu
      Pages 149-159
    3. Radu Bogdan Rusu
      Pages 161-175
    4. Radu Bogdan Rusu
      Pages 177-196
    5. Radu Bogdan Rusu
      Pages 197-200
  6. Back Matter
    Pages 0--1

About this book


The book written by Dr. Radu B. Rusu presents a detailed description of 3D Semantic Mapping in the context of mobile robot manipulation. As autonomous robotic platforms get more sophisticated manipulation capabilities, they also need more expressive and comprehensive environment models that include the objects present in the world, together with their position, form, and other semantic aspects, as well as interpretations of these objects with respect to the robot tasks.


The book proposes novel 3D feature representations called Point Feature Histograms (PFH), as well as frameworks for the acquisition and processing of Semantic 3D Object Maps with contributions to robust registration, fast segmentation into regions, and reliable object detection, categorization, and reconstruction. These contributions have been fully implemented and empirically evaluated on different robotic systems, and have been the original kernel to the widely successful open-source project the Point Cloud Library (PCL) -- see


3D Perception Mobile Manipulation Personal Robots Point Cloud Processing Robotics Semantic Mapping

Authors and affiliations

  1. 1.Open Perception, IncSan FranciscoUSA

Bibliographic information

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