IROS 2015 Paper Abstract


Paper WeAT2.4

Burri, Michael (ETH Zuerich), Oleynikova, Helen (ETH Zürich), Achtelik, Markus W. (ETH Zurich, Autonomous Syst. Lab), Siegwart, Roland (ETH Zurich)

Real-Time Visual-Inertial Mapping, Re-Localization and Planning Onboard MAVs in Unknown Environments

Scheduled for presentation during the Regular session "Unmanned Aerial Systems 4" (WeAT2), Wednesday, September 30, 2015, 09:15−09:30, Saal A4

2015 IEEE/RSJ International Conference on Intelligent Robots and Systems, Sept 28 - Oct 03, 2015, Congress Center Hamburg, Hamburg, Germany

This information is tentative and subject to change. Compiled on June 24, 2021

Keywords Unmanned Aerial Systems, Visual Navigation, Motion and Path Planning


In this work, we present a MAV system that is able to relocalize itself, create consistent maps and plan paths in full 3D in previously unknown environments. This is solely based on vision and IMU measurements with all components running onboard and in real-time. We use visual-inertial odometry to keep the MAV airborne safely locally, as well as for exploration of the environment based on high-level input by an operator. A globally consistent map is constructed in the background, which is then used to correct for drift of the visual odometry algorithm. This map serves as an input to our proposed global planner, which finds dynamic 3D paths to any previously visited place in the map, without the use of teach and repeat algorithms. In contrast to previous work, all components are executed onboard and in real-time without any prior knowledge about the environment.



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