Foundations and Trends® in
Robotics
Vol. 1, No. 1 (2010) 1–78
© 2009 D. Kragic and M. Vincze
DOI: 10.1561/2300000001
Vision for Robotics
Danica Kragic1 and Markus Vincze2
1 Centre for Autonomous Systems,
Computational Vision and Active Perception Lab, School of Computer
Science and Communication, KTH, Stockholm, 10044, Sweden, dani@kth.se
2 Vision for Robotics Lab, Automation and Control Institute, Technische Universitat Wien, Vienna, Austria, vincze@acin.tuwien.ac.at
SUGGESTED CITATION:
Danica Kragic and Markus Vincze (2010) “Vision for Robotics”,
Foundations and Trends® in Robotics: Vol. 1: No. 1, pp 1–78.
http:/dx.doi.org/10.1561/2300000001
Abstract
Robot vision refers to the capability of a robot to visually perceive the environment and use this information for execution of various tasks. Visual feedback has been used extensively for robot navigation and obstacle avoidance. In the recent years, there are also examples that include interaction with people and manipulation of objects. In this paper, we review some of the work that goes beyond of using artificial landmarks and fiducial markers for the purpose of implementing visionbased control in robots. We discuss different application areas, both from the systems perspective and individual problems such as object tracking and recognition.
1 Introduction 2
1.1 Scope and Outline 4
2 Historical Perspective 7
2.1 Early Start and Industrial Applications 7
2.2 Biological Influences and Affordances 9
2.3 Vision Systems 12
3 What Works 17
3.1 Object Tracking and Pose Estimation 18
3.2 Visual Servoing–Arms and Platforms 27
3.3 Reconstruction, Localization, Navigation, and Visual SLAM 32
3.4 Object Recognition 35
3.5 Action Recognition, Detecting, and Tracking Humans 42
3.6 Search and Attention 44
4 Open Challenges 48
4.1 Shape and Structure for Object Detection 49
4.2 Object Categorization 52
4.3 Semantics and Symbol Grounding: From Robot Task to Grasping and HRI 54
4.4 Competitions and Benchmarking 56
5 Discussion and Conclusion 59
Acknowledgments 64
References 65