Abstract
In this paper a scalable architecture with a computer vision subsystem as an integrated part to achieve a fast and robust navigation for almost autonomous mobile systems in dynamic environments is presented. The principal approach is not only using the robots’ mobile sensor systems but also some fixed external vision sensors to build the required environment models. The measurements of the mobile and external sensors are fused to improve the quality of the input data. This sensor fusion is done by an active dynamic environment model that also provides an optimised data layer for different path planning systems. To achieve the required system’s scalability a distributed approach is followed. Instead of using one big global environment model a distributed redundant environment model is employed to allow easier local path planning and to reduce bottlenecks in data transmission. Thus the path planning system is split to a local path planner and a global planning system.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Clint Bidlack, Arun Hampapur, and Arun Katkere. Visual robot navigation using flat earth obstacle projection. In IEEE International Conference on Robotics and Automation.
R. Gutsche, C. Laloni, and F.M. Wahl. Navigation und überwachung fahrerloser transportfahrzeuge durch ein hallen-sensorsystem. In Autonome Mobile System, 7. itFachgespräch.
Jason A. Janet, Ren C. Luo, and Michael G. Kay. The essential visibility graph: An approach to global motion planning for autonomous mobile robots. In IEEE International Conference on Robotics and Automation.
K.J. Kyriakopoulos and N.J. Krikelis P. Kakambouras. Navigation of nonholono-mic vehicles in complex environments with potential fields and tracking. In IEEE International Conference on Robotics and Automation.
C. Laloni. Globales Monitoring System zur Steuerung und Überwachung Fahrerloser Transportsysteme in Fabrikationsumgebungen. PhD thesis, Technische Universität Braunschweig, 1995.
C. Laloni, R. Gutsche, and F.M. Wahl. A factory-floor monitoring system for mobile robot guidance. In International Conference on Automation, Robotics and Computer Vision.
C. Laloni, R. Gutsche, and F.M. Wahl. Factory floor monitoring system with intelligent control for mobile robot guidance. In JSME International Conference on Advanced Mechatronics.
Aleksandar Timcenko and Peter Allen. Probability-driven motion planning for mobile robots. In IEEE International Conference on Robotics and Automation.
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 1999 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Steinhaus, P., Ehrenmann, M., Dillmann, R. (1999). MEPHISTO A Modular and Extensible Path Planning System Using Observation. In: Computer Vision Systems. ICVS 1999. Lecture Notes in Computer Science, vol 1542. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-49256-9_22
Download citation
DOI: https://doi.org/10.1007/3-540-49256-9_22
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-65459-9
Online ISBN: 978-3-540-49256-6
eBook Packages: Springer Book Archive