Abstract
In this work, we present a novel vision-based solution for operating a vehicle under Gaussian Distribution Temporal Logic (GDTL) constraints without global positioning infrastructure. We first present the mapping component that builds a high-resolution map of the environment by flying a team of two aerial vehicles in formation with sensor information provided by their onboard cameras. The control policy for the ground robot is synthesized under temporal and uncertainty constraints given the semantically labeled map. Finally, the ground robot executes the control policy given pose estimates from a dedicated aerial robot that tracks and localizes the ground robot. The proposed method is validated using a two-wheeled ground robot and a quadrotor with a camera for ten successful experimental trials.
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Notes
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Natural Point Optitrack: https://www.optitrack.com.
- 2.
DrRobot X80Pro: http://www.drrobot.com/products_item.asp?itemNumber=x80pro.
- 3.
Parrot Bebop: http://www.parrot.com/products/bebop-drone/.
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Acknowledgements
E. Cristofalo was supported in part by the 2015 National Defense Science and Engineering Graduate (NDSEG) fellowship. This work was also supported by US grants NSF CNS-1330008, NSF IIS-1350904, NSF NRI-1426907, NSF CMMI-1400167, ONR N00014-12-1-1000, and Spanish projects DPI2015-69376-R (MINECO/FEDER) and SIRENA (CUD2013-05). We are grateful for this support.
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Cristofalo, E., Leahy, K., Vasile, CI., Montijano, E., Schwager, M., Belta, C. (2017). Localization of a Ground Robot by Aerial Robots for GPS-Deprived Control with Temporal Logic Constraints. In: Kulić, D., Nakamura, Y., Khatib, O., Venture, G. (eds) 2016 International Symposium on Experimental Robotics. ISER 2016. Springer Proceedings in Advanced Robotics, vol 1. Springer, Cham. https://doi.org/10.1007/978-3-319-50115-4_46
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