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Approximate Sequential Optimization for Informative Path Planning (2402.08841v2)

Published 13 Feb 2024 in cs.RO

Abstract: We consider the problem of finding an informative path through a graph, given initial and terminal nodes and a given maximum path length. We assume that a linear noise corrupted measurement is taken at each node of an underlying unknown vector that we wish to estimate. The informativeness is measured by the reduction in uncertainty in our estimate, evaluated using several metrics. We present a convex relaxation for this informative path planning problem, which we can readily solve to obtain a bound on the possible performance. We develop an approximate sequential method where the path is constructed segment by segment through dynamic programming. This involves solving an orienteering problem, with the node reward acting as a surrogate for informativeness, taking the first step, and then repeating the process. The method scales to very large problem instances and achieves performance not too far from the bound produced by the convex relaxation. We also demonstrate our method's ability to handle adaptive objectives, multimodal sensing, and multi-agent variations of the informative path planning problem.

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References (24)
  1. “Sensor selection via convex optimization” In IEEE Transactions on Signal Processing 57.2 IEEE, 2008, pp. 451–462
  2. Shamak Dutta, Nils Wilde and Stephen L Smith “Informative Path Planning in Random Fields via Mixed Integer Programming” In IEEE Conference on Decision and Control (CDC), 2022, pp. 7222–7228 IEEE
  3. “Nonmyopic informative path planning in spatio-temporal models” In AAAI Conference on Artificial Intelligence (AAAI) 10.4, 2007, pp. 16–7
  4. “An informative path planning framework for UAV-based terrain monitoring” In Autonomous Robots 44.6 Springer, 2020, pp. 889–911
  5. Andreas Krause, Ajit Singh and Carlos Guestrin “Near-optimal sensor placements in Gaussian processes: Theory, efficient algorithms and empirical studies” In Journal of Machine Learning Research 9.2, 2008
  6. “Efficient informative sensing using multiple robots” In Journal of Artificial Intelligence Research 34, 2009, pp. 707–755
  7. “Motion Planning Under Uncertainty with Complex Agents and Environments via Hybrid Search” In Journal of Artificial Intelligence Research 75, 2022, pp. 1–81
  8. Christer Bäckström, Peter Jonsson and Sebastian Ordyniak “Cost-Optimal Planning, Delete Relaxation, Approximability, and Heuristics” In Journal of Artificial Intelligence Research 70, 2021, pp. 169–204
  9. “Adaptive continuous-space informative path planning for online environmental monitoring” In Journal of Field Robotics 34.8 Wiley Online Library, 2017, pp. 1427–1449
  10. Per Boström-Rost, Daniel Axehill and Gustaf Hendeby “On global optimization for informative path planning” In IEEE Control Systems Letters 2.4 IEEE, 2018, pp. 833–838
  11. Sisi Song, Abel Rodriguez and Mircea Teodorescu “Trajectory planning for autonomous nonholonomic vehicles for optimal monitoring of spatial phenomena” In International Conference on Unmanned Aircraft Systems, 2015, pp. 40–49 IEEE
  12. Roman Marchant, Fabio Ramos and Scott Sanner “Sequential Bayesian optimisation for spatial-temporal monitoring” In Conference on Uncertainty in Artificial Intelligence (UAI), 2014, pp. 553–562
  13. Philippe Morere, Roman Marchant and Fabio Ramos “Sequential Bayesian optimization as a POMDP for environment monitoring with UAVs” In IEEE International Conference on Robotics and Automation (ICRA), 2017, pp. 6381–6388
  14. Philippe Morere, Roman Marchant and Fabio Ramos “Continuous state-action-observation POMDPs for trajectory planning with Bayesian optimisation” In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2018, pp. 8779–8786
  15. “Informative path planning to estimate quantiles for environmental analysis” In IEEE Robotics and Automation Letters IEEE, 2022
  16. Julius Rückin, Liren Jin and Marija Popović “Adaptive informative path planning using deep reinforcement learning for UAV-based active sensing” In IEEE International Conference on Robotics and Automation (ICRA), 2022
  17. Joshua Ott, Edward Balaban and Mykel J Kochenderfer “Sequential Bayesian Optimization for Adaptive Informative Path Planning with Multimodal Sensing” In IEEE International Conference on Robotics and Automation (ICRA), 2023, pp. 7894–7901 IEEE
  18. Shushman Choudhury, Nate Gruver and Mykel J Kochenderfer “Adaptive informative path planning with multimodal sensing” In International Conference on Automated Planning and Scheduling (ICAPS) 30, 2020, pp. 57–65
  19. Mykel J Kochenderfer and Tim A Wheeler “Algorithms for Optimization” MIT Press, 2019
  20. Clair E Miller, Albert W Tucker and Richard A Zemlin “Integer programming formulation of traveling salesman problems” In Journal of the ACM (JACM) 7.4 ACM New York, NY, USA, 1960, pp. 326–329
  21. Stephen P Boyd and Lieven Vandenberghe “Convex Optimization” Cambridge University Press, 2004
  22. Pieter Vansteenwegen, Wouter Souffriau and Dirk Van Oudheusden “The orienteering problem: A survey” In European Journal of Operational Research 209.1 Elsevier, 2011, pp. 1–10
  23. Aldy Gunawan, Hoong Chuin Lau and Pieter Vansteenwegen “Orienteering problem: A survey of recent variants, solution approaches and applications” In European Journal of Operational Research 255.2 Elsevier, 2016, pp. 315–332
  24. Steven Diamond, Reza Takapoui and Stephen Boyd “A general system for heuristic minimization of convex functions over non-convex sets” In Optimization Methods and Software 33.1 Taylor & Francis, 2018, pp. 165–193
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