Localization of a Ground Robot by Aerial Robots for GPS-Deprived Control with Temporal Logic Constraints
- 3.1k Downloads
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.
KeywordsVision-based localization Temporal logic planning Air-ground localization Heterogeneous robot systems
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.
- 2.Vasile, C.I., Leahy, K., Cristofalo, E., Jones, A., Schwager, M., Belta, C.: Control in belief space with temporal logic specifications. In: Proceedings of the 2016 Conference on Decision and Control (CDC). IEEE (2016, to appear)Google Scholar
- 3.Vaughan, R.T., Sukhatme, G.S., Mesa-Martinez, F.J., Montgomery, J.F.: Fly spy: lightweight localization and target tracking for cooperating air and ground robots. In: Distributed Autonomous Robotic Systems 4, pp. 315–324. Springer, Japan (2000)Google Scholar
- 5.Forster, C., Pizzoli, M., Scaramuzza, D.: Air-ground localization and map augmentation using monocular dense reconstruction. In: Proceedings of the 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 3971–3978. IEEE (2013)Google Scholar
- 6.Thrun, S., Leonard, J.J.: Simultaneous localization and mapping. In: Springer Handbook of Robotics, pp. 871–889. Springer, Heidelberg (2008)Google Scholar
- 7.Newcombe, R.A., Lovegrove, S.J., Davison, A.J.: DTAM: dense tracking and mapping in real-time. In: Proceedings of the 2011 International Conference on Computer Vision (ICCV), pp. 2320–2327. IEEE (2011)Google Scholar
- 8.Benhimane, S., Malis, E.: Homography-based 2d visual servoing. In: Proceedings of the 2006 International Conference on Robotics and Automation (ICRA), pp. 2397–2402. IEEE (2006)Google Scholar
- 10.Ma, Y., Soatto, S., Kosecka, J., Sastry, S.S.: An Invitation to 3-d Vision: From Images to Geometric Models, vol. 26. Springer Science & Business Media, New York (2012)Google Scholar
- 11.Quigley, M., Conley, K., Gerkey, B., Faust, J., Foote, T., Leibs, J., Wheeler, R., Ng, A.Y.: ROS: an open-source robot operating system. In: ICRA Workshop on Open Source Software, vol. 3, p. 5 (2009)Google Scholar
- 12.Monajjemi, M.: Bebop autonomy (2015). https://github.com/AutonomyLab/bebop_autonomy
- 13.Bradski, G., et al.: The opencv library. Doctor Dobbs J. 25(11), 120–126 (2000)Google Scholar