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AMS
2007
Springer

Autonomous Exploration for 3D Map Learning

10 years 9 months ago
Autonomous Exploration for 3D Map Learning
Abstract. Autonomous exploration is a frequently addressed problem in the robotics community. This paper presents an approach to mobile robot exploration that takes into account that the robot acts in the three-dimensional space. Our approach can build compact three-dimensional models autonomously and is able to deal with negative obstacles such as abysms. It applies a decision-theoretic framework which considers the uncertainty in the map to evaluate potential actions. Thereby, it trades off the cost of executing an action with the expected information gain taking into account possible sensor measurements. We present experimental results obtained with a real robot and in simulation.
Dominik Joho, Cyrill Stachniss, Patrick Pfaff, Wol
Added 07 Jun 2010
Updated 07 Jun 2010
Type Conference
Year 2007
Where AMS
Authors Dominik Joho, Cyrill Stachniss, Patrick Pfaff, Wolfram Burgard
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