ICRA 2011 Paper Abstract


Paper TuP214.4

Heng, Lionel (ETH Zurich), Meier, Lorenz (ETH Zurich), Tanskanen, Petri (ETH Zurich), Fraundorfer, Friedrich (ETH Zurich), Pollefeys, Marc (ETH Zurich)

Autonomous Maneuvering and Obstacle Avoidance on a Vision-Guided MAV Using On-Board Processing

Scheduled for presentation during the Regular Sessions "Visual Navigation IV" (TuP214), Tuesday, May 10, 2011, 16:10−16:25, Room 5J

2011 IEEE International Conference on Robotics and Automation, May 9-13, 2011, Shanghai International Conference Center, Shanghai, China

This information is tentative and subject to change. Compiled on April 2, 2020

Keywords Visual Navigation, Autonomous Navigation, Aerial Robotics


We present a novel stereo-based obstacle avoidance system on a vision-guided micro air vehicle (MAV) that is capable of fully autonomous maneuvers in unknown and dynamic environments. All algorithms run exclusively on the vehicle’s on-board computer, and at high frequencies that allow the MAV to react quickly to obstacles appearing in its flight trajectory. Our MAV platform is a quadrotor aircraft equipped with an inertial measurement unit and two stereo rigs. An obstacle mapping algorithm processes stereo images, producing a 3D map representation of the environment; at the same time, a dynamic anytime path planner plans a collision-free path to a goal point.



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