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An accurate and efficient navigation system for omnidirectional robots in industrial environments

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Abstract

Enhanced logistics is widely regarded as a key technology to increase flexibility and cost efficiency of today’s factories. For example, fully autonomous transport vehicles aim to gradually replace conveyor belts, guided vehicles, and manual labor. In this context, especially omnidirectional robots are appealing thanks to their advanced maneuvering capabilities. In industrial applications, however, accuracy as well as safety and efficiency are key requirements for successful navigation systems. In this paper, we present an accurate navigation system for omnidirectional robots. Our system includes dedicated modules for mapping, localization, trajectory generation and robot control. It has been designed for accurate execution by devising smooth, curvature continuous trajectories, by planning appropriate velocities and by accounting for platform and safety constraints. In this way, it completely utilizes the maneuvering capabilities of omnidirectional robots and optimizes trajectories with respect to time of travel. We present extensive experimental evaluations in simulation and in changing real-world environments to demonstrate the robustness and accuracy of our system.

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Notes

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  2. Frog AGV Systems. http://frog.nl, 2014. Online, accessed 2014-11-26.

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Acknowledgments

This work has partly been supported by the European Commission under Grant Agreement Numbers FP7-248258-First-MM, FP7-260026-TAPAS, and FP7-248873-RADHAR.

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Authors and Affiliations

  1. Department of Computer Science, University of Freiburg, Freiburg im Breisgau, Germany

    Christoph Sprunk, Boris Lau & Wolfram Burgard

  2. KUKA Laboratories GmbH, Augsburg, Germany

    Patrick Pfaff

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  1. Christoph Sprunk
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  2. Boris Lau
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  4. Wolfram Burgard
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Correspondence to Christoph Sprunk.

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Sprunk, C., Lau, B., Pfaff, P. et al. An accurate and efficient navigation system for omnidirectional robots in industrial environments. Auton Robot 41, 473–493 (2017). https://doi.org/10.1007/s10514-016-9557-1

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