Leaving flatland: toward real-time 3D navigation

Authors:
Benoit Morisset;Radu Bogdan Rusu;Aravind Sundaresan;Kris Hauser;Motilal Agrawal;Jean-Claude Latombe;Michael Beetz
Affiliations:
Artificial Intelligence Center, SRI International, Menlo Park, CA;Intelligent Autonomous Systems, Technische Universität München, München, Germany;Artificial Intelligence Center, SRI International, Menlo Park, CA;Computer Science Department, Stanford University, Stanford, CA;Artificial Intelligence Center, SRI International, Menlo Park, CA;Computer Science Department, Stanford University, Stanford, CA;Intelligent Autonomous Systems, Technische Universität München, München, Germany
Venue:
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Year:
2009

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Abstract

We report our first experiences with Leaving Flatland, an exploratory project that studies the key challenges of closing the loop between autonomous perception and action on challenging terrain. We propose a comprehensive system for localization, mapping, and planning for the RHex mobile robot in fully 3D indoor and outdoor environments. This system integrates Visual Odometry-based localization with new techniques in real-time 3D mapping from stereo data. The motion planner uses a new decomposition approach to adapt existing 2D planning techniques to operate in 3D terrain. We test the map-building and motion-planning subsystems on real and synthetic data, and show that they have favorable computational performance for use in high-speed autonomous navigation.