Abstract
We present information theoretic search strategies for single and multi-robot teams to localize the source of a chemical spill in turbulent flows. In this work, robots rely on sporadic and intermittent sensor readings to synthesize information maximizing exploration strategies. Using the spatial distribution of the sensor readings, robots construct a belief distribution for the source location. Motion strategies are designed to maximize the change in entropy of this belief distribution. In addition, we show how a geophysical description of the environmental dynamics can improve existing motion control strategies. This is especially true when process and vehicle dynamics are intricately coupled with the environmental dynamics. We conclude with a summary of current efforts in robotic tracking of coherent structures in geophysical flows. Since coherent structures enables the prediction and estimation of the environmental dynamics, we discuss how this geophysical perspective can result in improved control strategies for autonomous systems.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
Notes
- 1.
For full animation visit http://earth.nullschool.net/ and http://svs.gsfc.nasa.gov/vis/a000000/a003800/a003827/.
- 2.
Noise can arise from uncertainty in model parameters and/or measurement noise.
References
Charrow, B., Michael, N., Kumar, V.: Cooperative Multi-robot Estimation and Control for Radio Source Localization. Springer International Publishing, New York (2013)
Crisan, D., Doucet, A.: A survey of convergence results on particle filtering methods for practitioners. IEEE Trans. Signal Process. 50(3), 736–746 (2002)
Fabregat, A., Dewar, W.K., Ozgokmen, T.M., Poje, A.C., Wienders, N.: Numerical simulations of turbulent thermal, bubble and hybrid plumes. Ocean Model. 90, 16–28 (2015)
Forgoston, E., Billings, L., Yecko, P., Schwartz, I.B.: Set-based corral control in stochastic dynamical systems: making almost invariant sets more invariant. Chaos 21, 013116 (2011)
Haller, G.: A variational theory of hyperbolic Lagrangian coherent structures. Phys. D 240, 574–598 (2011)
Haller, G., Yuan, G.: Lagrangian coherent structures and mixing in two-dimensional turbulence. Phys. D 147, 352–370 (2000)
Heckman, C.R., Hsieh, M.A., Schwartz, I.B.: Controlling basin breakout for robots operating in uncertain flow environments. In: International Symposium on Experimental Robotics (ISER 2014), Marrakech/Essaouira, Morocco (2014)
Hoffmann, G., Tomlin, C.: Mobile sensor network control using mutual information methods and particle filters. IEEE Trans. Autom. Control 55(1), 32–47 (2010)
Hsieh, M.A., Forgoston, E., Mather, T.W., Schwartz, I.: Robotic manifold tracking of coherent structures in flows. In: Proceedings of IEEE International Conference on Robotics and Automation (ICRA2012), Minneapolis, MN USA (2012)
Hsieh, M.A., Mallory, K., Schwartz, I.B.: Distributed allocation of mobile sensing agents in geophysical flows. In: Proceedings of the 2014 American Controls Conference, Portland, OR (2014)
Huber, M., Bailey, T., Durrant-Whyte, H., Hanebeck, U.: On entropy approximation for gaussian mixture random vectors. In: IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems, 2008. MFI 2008, pp. 181–188 (2008). doi:10.1109/MFI.2008.4648062
Inanc, T., Shadden, S., Marsden, J.: Optimal trajectory generation in ocean flows. In: Proceedings of the American Control Conference, pp 674–679 (2005)
Kularatne, D., Hsieh, A.: Tracking attracting lagrangian coherent structures in flows. In: Proceedings of Robotics: Science and Systems, Rome, Italy (2015)
Levy, M., Ferrari, R., Franks, P.J.S., Martin, A.P., Riviere, P.: Bringing physics to life at the submesoscale. Geophys. Res. Lett. 39(14) (2012)
Lolla, T., Ueckermann, M.P., Haley, P., Lermusiaux, P.F.J.: Path planning in time dependent flow fields using level set methods. In: Proceedings of IEEE International Conference on Robotics and Automation, Minneapolis, MN, USA (2012)
Mallory, K., Hsieh, M.A., Forgoston, E., Schwartz, I.B.: Distributed allocation of mobile sensing swarms in gyre flows. Nonlin. Process. Geophys. 20(5), 657–668 (2013)
Michini, M., Hsieh, M.A., Forgoston, E., Schwartz, I.B.: Experimental validation of robotic manifold tracking in gyre-like flows. In: Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2014, Chicago, IL, USA (2014)
Michini, M., Hsieh, M.A., Forgoston, E., Schwartz, I.B.: Robotic tracking of coherent structures in flows. IEEE Trans. Robot. 30(3), 593–603 (2014)
Michini, M., Rastgoftar, H., Hsieh, M.A., Jayasuriya, S.: Distributed formation control for collaborative tracking of manifolds in flows. In: Proceedings of the 2014 American Control Conference (ACC 2014), Portland, OR (2014)
Mier-y Teran-Romero, L., Forgoston, E., Schwartz, I.: Coherent pattern prediction in swarms of delay-coupled agents. IEEE Trans. Robot. 28(5), 1034–1044 (2012)
Russell, R.: Locating underground chemical sources by tracking chemical gradients in 3 dimensions. In: Proceedings of 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2004 (IROS 2004), vol. 1, pp 325–330 (2004). doi:10.1109/IROS.2004.1389372
SCRIPPS: Naitonal HF RADAR network - surface currents (2014). URL http://cordc.ucsd.edu/projects/mapping/maps/
Senatore, C., Ross, S.: Fuel-efficient navigation in complex flows. Am. Control Conf. 2008, 1244–1248 (2008)
Shadden, S.C., Lekien, F., Marsden, J.E.: Definition and properties of Lagrangian coherent structures from finite-time Lyapunov exponents in two-dimensional aperiodic flows. Phys. D Nonlin. Phenom. 212(3–4), 271–304 (2005)
Shchepetkin, A., McWilliams, J.: Quasi-monotone advection schemes based on explicit locally adaptive dissipation. Mon. Weather Rev. 126, 1541–1580 (1998)
Shchepetkin, A.F., McWilliams, J.C.: The regional oceanic modeling system (ROMS): a split-explicit, free-surface, topography-following-coordinate oceanic model. Ocean Model. 9, 347–404 (2005)
Smith, R.N., Chao, Y., Li, P.P., Caron, D.A., Jones, B.H., Sukhatme, G.S.: Planning and implementing trajectories for autonomous underwater vehicles to track evolving ocean processes based on predictions from a regional ocean model. Int. J. Robot. Res. 29(12), 1475–1497 (2010)
Smith, R., Kelly, J., Sukhatme, G.: Towards improving mission execution for autonomous gliders with an ocean model and kalman filter. In: Proceedings of the IEEE International Conference on Robotics and Automation, Minneapolis, MN (2012)
Taylor, G.: Dispersion of soluble matter in solvent flowing slowly through a tube. Proc. R Soc. Lond. A A219, 186–203 (1953)
Vergassola, M., Villermaux, E., Shraiman, B.I.: Infotaxis as a strategy for searching without gradients. Nature 445, 406–409 (2007)
Veronis, G.: Wind-driven ocean circulation, part I and part II. Deep-Sea Res. 13, 31 (1966)
Acknowledgements
MAH, HH, and DK are supported by ONR Award Nos. N000141211019 and N000141310731 and National Science Foundation (NSF) grant IIS-1253917. EF and PAY are supported by National Science Foundation (NSF) grant DMS-1418956. IBS is supported by ONR contract No. N0001412WX2003 and NRL 6.1 program contract No. N0001412WX30002. We would like to thank Alex Fabregat Tomas (CUNY) and Andrew Poje (CUNY) in providing the plume data.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG
About this chapter
Cite this chapter
Ani Hsieh, M. et al. (2018). Small and Adrift with Self-Control: Using the Environment to Improve Autonomy. In: Bicchi, A., Burgard, W. (eds) Robotics Research. Springer Proceedings in Advanced Robotics, vol 3. Springer, Cham. https://doi.org/10.1007/978-3-319-60916-4_22
Download citation
DOI: https://doi.org/10.1007/978-3-319-60916-4_22
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-60915-7
Online ISBN: 978-3-319-60916-4
eBook Packages: EngineeringEngineering (R0)