Appearance-Based Obstacle Detection with Monocular Color Vision
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
Interactive humanoid robots for a science museum
Proceedings of the 1st ACM SIGCHI/SIGART conference on Human-robot interaction
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 03
Robust Object Detection with Interleaved Categorization and Segmentation
International Journal of Computer Vision
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Information retrieval system for human-robot communication: asking for directions
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
The autonomous city explorer project
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Robots asking for directions: the willingness of passers-by to support robots
Proceedings of the 5th ACM/IEEE international conference on Human-robot interaction
Autonomous behavior-based switched top-down and bottom-up visual attention for mobile robots
IEEE Transactions on Robotics
A wearable navigation system for visually impaired users
Proceedings of the 6th International Conference on Rehabilitation Engineering & Assistive Technology
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In the Autonomous City Explorer (ACE) project a mobile robot is developed, which is capable of finding its way to a given destination in an unknown urban environment. An exemplary mission is to find the way from our institute to the Marienplatz, a public place in the center of Munich, without any prior knowledge or GPS information. Inspired by the behavior of humans in unknown environments, ACE must find its way by asking pedestrians. The route is about 1.5 kilometers far and includes heavily traveled roads and crowded public places. In order to navigate safely in an unknown urban environment, some challenges arise for the vision system. Robust human detection, tracking and the estimation of human body poses is essential for natural interaction with pedestrians. Furthermore, the robot needs to be able to detect sidewalk and crossroads. A visual odometry system is used to support the conventional navigation. Outdoor experiments were conducted twice successfully. After about 5 hours and interacting with 25 and 38 persons respectively, ACE arrived the Marienplatz. This paper describes both, an architecture of the vision system used for ACE and the algorithms used to deal with the described challenges.