Towards Semantic Maps for Mobile Robots

Andreas Nüchter and Joachim Hertzberg. Towards Semantic Maps for Mobile Robots. Journal of Robotics and Autonomous Systems (JRAS), Special Issue on Semantic Knowledge in Robotics, Elsevier Science, Volume 56, Issue 11, ISSN 0921-8890, pages 915-926, 2008.

Intelligent autonomous action in ordinary environments calls for 3D maps. 3D geometry is necessary for avoiding collision with complex obstacles and to self localize in six degrees of freedom (6 DoF) (x, y, z positions, roll, yaw, and pitch angles). Meaning, in addition to geometry, becomes inevitable if the robot is supposed to interact with its environment in a goal-directed way. A semantic stance enables the robot to reason about objects; it helps disambiguate or round off sensor data; and the robot knowledge becomes reviewable and communicable.
The paper describes an approach and a completed robot system for semantic mapping. The prime sensor is a 3D laser scanner. Individual scans are registered into a coherent 3D geometry map by 6D SLAM. Coarse scene features (e.g., walls, floors in a building) are determined by semantic labeling. More delicate objects are then detected by a trained classifier and localized. In the end, the semantic maps can be visualized for human inspection. We sketch the overall architecture of the approach, explain the respective steps and their underlying algorithms, give examples based on a working robot implementation, and discuss the findings.

Category:

Science & Technology

Tags:

• 3D mapping
• robotics
• semantic maps
• SLAM