Abstract
Terrestrial planetary bodies such as Mars and the Moon are known to harbor volcanic terrain with enclosed lava tube conduits and caves. The shielding from cosmic radiation that they provide makes them a potentially hospitable habitat for life. This motivates the need to explore such lava tubes and assess their potential as locations for future human outposts. Such exploration will likely be conducted by autonomous mobile robots before humans, and this paper proposes a novel mechanism for constructing maps of lava tubes using a multi-robot platform. A key issue in mapping lava tubes is the presence of fine sand that can be found at the bottom of most tubes, as observed on earth. This fine sand makes robot odometry measurements highly prone to errors. To address this issue, this work leverages the ability of a multi-robot system to measure the relative motion of robots using laser range finders. Mounted on each robot is a 2D laser range finder attached to a servo to enable 3D scanning. The lead robot has an easily recognized target panel that allows the follower robot to measure both the relative distance and orientation between robots. First, these measurements are used to enable 2D (SLAM) of a lava tube. Second, the 3D range measurements are fused with the 2D maps via ICP algorithms to construct full 3D representations. This method of 3D mapping does not require odometry measurements or fine-scale environment features. It was validated in a building hallway system, demonstrating successful loop closure and mapping errors on the order of 0.63 m over a 79.64 m long loop. Error growth models were determined experimentally that indicate the robot localization errors grow at a rate of 20 mm per meter travelled, although this is also dependent on the relative orientation of robots localizing each other. Finally, the system was deployed in a lava tube located at Pisgah Crater in the Mojave Desert, CA. Data was collected to generate a full 3D map of the lava tube. Comparison with known measurements taken between two ends of the lava tube indicates the mapping errors were on the order of 1.03 m after the robot travelled 32 m.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Aulinas, J., et al.: The SLAM problem: a survey. In: Proceedings of the 2008 Conference on Artificial Intelligence Research and Development: Proceedings of the 11th International Conference of the Catalan Association for Artificial Intelligence, pp. 363–371 (2008)
Besl, P.J., et al.: Method for registration of 3-D shapes. In: Robotics-DL Tentative. International Society for Optics and Photonics, pp. 586–606 (1992)
Borrmann, D., et al.: Globally consistent 3D mapping with scan matching. Robot. Auton. Syst. 56 (2), 130–142 (2008)
Bosse, M., et al.: Continuous 3D scan-matching with a spinning 2D laser. In: ICRA’09. IEEE International Conference on Robotics and Automation, pp. 4312–4319 (2009)
Burgard, W., et al.: Collaborative multi-robot exploration. In: Proceedings. ICRA’00. IEEE International Conference on Robotics and Automation, vol. 1, pp. 476–481 (2000)
Chen, Y., et al.: Object modeling by registration of multiple range images. In: Proceedings of the IEEE International Conference on Robotics and Automation, pp. 2724–2729 (1991)
Fenwick, J., et al.: Cooperative concurrent mapping and localization. In: Proceedings. ICRA’02. IEEE International Conference on Robotics and Automation, 2002, vol. 2, pp. 1810–1817 (2002)
Fischer, D., Kohlhepp, P.: 3D geometry reconstruction from multiple segmented surface descriptions using neuro-fuzzy similarity measures. J. Intell. Rob. Syst. 29(4), 389–431 (2000)
Henry, P., et al.: RGB-D mapping: using depth cameras for dense 3d modeling of indoor environments. Exp. Robot. Springer Tracts Adv. Robot. 79, 477–491 (2014)
Huber, D.F., Vandapel. N.: Automatic three-dimensional underground mine mapping. IJRR 25(1), 7–17 (2006)
Leveille, R., et al.: Lava tubes and basaltic caves as astrobiological targets on earth and mars: a review. Planet. Space Sci. 58, 592 (2012)
Lucchese, L., et al.: A frequency domain technique for range data registration. IEEE Trans. Pattern Anal. Mach. Intell. 24, 1468–1484 (2002)
Magnusson, M., et al.: Scan registration for autonomous mining vehicles using 3D-NDT. J. Field Robot. 10(24), 803–827 (2007)
Nutcher, H., et al.: 6D SLAM-3D mapping outdoor environments. J. Field Robot. 24, 699–722 (2007)
Pathak, K., et al.: Fast registration based on noisy planes with unknown correspondences for 3D mapping. IEEE Trans. Robt. 26, 424–441 (2010)
Pomerleau, F., et al.: Comparing ICP variants on real-world data sets. Auton. Robot. 34(3), 133–148 (2013)
Rekleitis, I., Dudek, G., Milios, E.: Multi-robot collaboration for robust exploration. Ann. Math. Artif. Intell. 31, 7–40 (2001)
Scheding, S.: Experiments in autonomous underground guidance. In: Proceedings, 1997 IEEE International Conference on Robotics and Automation, 1997, vol.3, pp. 1898–1903 (1997)
Thrun, S., et al.: A real-time algorithm for mobile robot mapping with applications to multi-robot and 3d mapping. In: IEEE International Conference on Robotics and Automation, 2000. Proceedings. ICRA’00, vol. 1, pp. 321–328 (2000)
Thrun, S., et al.: Simultaneous localization and mapping with sparse extended information filters. Algorithmic Found. Robot. V 7, 363–380 (2004)
Tong, C., et al.: Three-dimensional SLAM for mapping planetary work site environments. J. Field Robot. 29, 381–412 (2012)
Vaskevicius, N., et al.: Efficient representation in 3D environment modeling for planetary robotic exploration. Adv. Robot. 24, 1169–1197 (2010)
Weingarten, J., et al.: EKF-based 3D SLAM for structured environment reconstruction. In: IEEE 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2005. (IROS 2005), pp. 3834–3839 (2005)
Zlot, R., Bosse, M.: Efficient large-scale 3D mobile mapping and surface reconstruction of an underground mine. Field Serv. Robot.: Springer Tracts Adv. Robot. 92, 479–493 (2012)
Acknowledgments
The authors would like to thank all the people who contributed to the project: Samuel Yim, Shreyasha Paudel, Phuong Nguyen, Sean Messenger and Kevin Smith.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this chapter
Cite this chapter
Huang, X., Yang, J., Storrie-Lombardi, M., Lyzenga, G., Clark, C.M. (2016). Multi-robot Mapping of Lava Tubes. In: Wettergreen, D., Barfoot, T. (eds) Field and Service Robotics. Springer Tracts in Advanced Robotics, vol 113. Springer, Cham. https://doi.org/10.1007/978-3-319-27702-8_31
Download citation
DOI: https://doi.org/10.1007/978-3-319-27702-8_31
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-27700-4
Online ISBN: 978-3-319-27702-8
eBook Packages: EngineeringEngineering (R0)