ICRA'09 Paper Abstract

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Paper FrC10.4

Ahrens, Spencer (Massachusetts Institute of Technology), Levine, Daniel S (Massachusetts Institute of Technology), Andrews, Gregory (Charles Stark Draper Laboratory, Inc.), How, Jonathan (Massachusetts Institute of Technology)

Vision-Based Guidance and Control of a Hovering Vehicle in Unknown, GPS-Denied Environments

Scheduled for presentation during the Regular Sessions "Visual Navigation - II" (FrC10), Friday, May 15, 2009, 14:30−14:50, Room: 502

2009 IEEE International Conference on Robotics and Automation, May 12 - 17, 2009, Kobe, Japan

This information is tentative and subject to change. Compiled on January 24, 2022

Keywords Visual Navigation, Reactive and Sensor-Based Planning, Computer Vision for Robotics and Automation

Abstract

This paper describes the system architecture and core algorithms for a quadrotor helicopter that uses vision data to navigate an unknown, indoor, GPS-denied environment. Without external sensing, an estimation system that relies only on integrating inertial data will have rapidly drifting position estimates. Micro aerial vehicles (MAVs) are stringently weight -constrained, leaving little margin for additional sensors beyond the mission payload. The approach taken in this paper is to introduce an architecture that exploits a common mission payload, namely a video camera, as a dual-use sensor to aid in navigation. Several core algorithms, including a fast environment mapper and a novel heuristic for obstacle avoidance, are also presented. Finally, drift-free hover and obstacle avoidance flight tests in a controlled environment are presented and analyzed.

 

 

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