Repository for sharing and documenting papers on robotic exploration in navigable environments. Includes papers which discuss mapping techniques while exploring environments in order to build insitu-models.
For completeness, the citations and brief descriptions of each paper can be found below. To find the matching paper in the repository, you can search by authorlastname-year-affiliation-shortenedtitle.
S. Arora and S. Scherer, "Randomized algorithm for informative path planning with budget constraints," Robotics and Automation, 2017 IEEE International Conference on, IEEE, 2017.
Linking to this information, this ICRA paper presents the Randomized Anytime Orienteering algorithm which is claimed to be a near-optimal solver for a best informative path in an environment. The agorithm leverages random and biased sampling, the TPS problem, and greedy search to make optimal path choices from a set of start, end, and intermediary nodes.
H. Carillo, P. Dames, V. Kumar, and J. A. Castellanos, "Autonomous robotic exploration using occupancy grid maps and graph slam based on shannon and renyi entropy," Robotics and Automation, 2015 IEEE International Conference on, IEEE, 2015.
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A. Das et al., “Mapping, planning, and sample detection strategies for autonomous exploration,” J. F. Robot., vol. 31, no. 1, 2014.
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H. El-Hussieny, S. F. Assal, and M. Abdellatif, "Robotic exploration: new heuristic backtracking algorithm, performance evalutation and complexity metric," International Journal of Advanced Robotic Systems, vol. 12, no. 4, 2015.
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E. Galceran and M. Carreras, “A survey on coverage path planning for robotics,” Rob. Auton. Syst., vol. 61, no. 12, 2013.
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Y. Girdhar and G. Dudek, "Modeling curiousity in a mobile robot for long-term autonomous exploration and monitoring," Autonomous Robotics, 2016.
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M. B. Hafez and C. K. Loo, "Topological Q-learning with internally guided exploration for mobile robot navigation," Neural Computing and Applications, vol. 26, no. 8, pp. 1939-1954, 2015.
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R. Houthooft, X. Chen, Y. Duan, and J. Schulman, "VIME: Variational information maximizing exploration," Advances in Neural Information Processing Systems, 2016.
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R. Houthooft, X. Chen, Y. Duan, J. Shulman, F. De Turck, and P. Abbeel, "Curiosity-driven exploration in deep reinforcement learning via bayesian exploration in deep reinforcement learning via bayesian neural networks," arXiv, 2016.
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S. Isler, R. Sabzevari, J. Delmerico, and D. Scaramuzza, "An information gain formulation for active volumetic 3d reconstruction," Robotics and Automation, 2016 IEEE Conference on, IEEE, 2016.
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S. Jain, S. Nuske, A. Chambers, L. Yoder, H. Cover, L. Chamberlain, S. Scherer, and S. Singh, "Autonomous river exploration," Field and Service Robotics, Springer International Publishing, pp. 93-106, 2015.
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I. Kostavelis and A. Gasteratos, “Semantic mapping for mobile robotics tasks: A survey,” Rob. Auton. Syst., vol. 66, 2015.
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X. Lan, and M. Schwager, "Rapdily exploring random cycles: persistent estimation for spatiotemporal fields with multiple sensing robots," IEEE Tranactions on Robotics, vol. 32, no. 5, pp. 1230-1244, 2016.
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M. Lauri, and R. Ritala, "Planning for robotic exploration based on forward simulation," Robotics and Autonomous Systems, vol. 83, pp. 15-31, 2016.
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R. Marchant and F. Ramos, “Bayesian Optimisation for informative continuous path planning,” in Proceedings - IEEE International Conference on Robotics and Automation, 2014, pp. 6136–6143.
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R. Marchant, F. Ramos, and S. Sanner, “Sequential Bayesian Optimisation for Spatial-Temporal Monitoring,” Conf. Uncertain. Artif. Intell., 2014.
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P. Morere, R. Marchant, and F. Ramos, “Sequential Bayesian optimization as a POMDP for environment monitoring with UAVs,” in Proceedings - IEEE International Conference on Robotics and Automation, 2017.
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S. Oswald, M. Bennewitz, W. Burgard, and C. Stachniss, "Speeding-up robot exploration by exploiting background information," IEEE Robotics and Automation Letters, vol. 1, no. 2, pp. 716-732, 2016.
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P. Perdikaris, D. Venturi, J. O. Royset, and G. E. Karniadakis, "Multi-fidelity modeling via recursive co-kriging and gaussian-markov random fields," Proc. R. Soc. A, vol. 471, no. 2179, 2015.
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M. Popovic, G. Hitz, J. Nieto, I. Sa, R. Siegwart, and E. Galceran, “Online informative path planning for active classification using UAVs,” in Proceedings - IEEE International Conference on Robotics and Automation, 2017.
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S. A. Sadat, J. Wawerla, and R. T. Vaughan, “Recursive non-uniform coverage of unknown terrains for UAVs,” in IEEE International Conference on Intelligent Robots and Systems, 2014.
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S. Salan, E. Drumwright, and K. I. Lin, "Minimum energy robotic exploration: A formulation and an approach," IEEE Transactions on Systems, Man, And Cybernetics, vol. 45, no. 1, pp. 175-182, 2015.
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J. M. Santos, T. Krajnik, J. P. Fentanes, and T. Duckett, "Lifelong information-driven exploration to complete and refine 4d spatio-temporal maps," IEEE Robotics and Automation Letters, vol. 1, no. 2, pp. 684-691, 2016.
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A. Singla, E. Horvitz, P. Kohli, R. White, and A. Krause, “Information gathering in networks via active exploration,” in IJCAI International Joint Conference on Artificial Intelligence, 2015, vol. 2015–January.
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J. R. Souza, R. Marchant, L. Ott, D. F. Wolf, and F. Ramos, “Bayesian optimisation for active perception and smooth navigation,” in Proceedings - IEEE International Conference on Robotics and Automation, 2014.
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D. P. Strom, F. Nenci, and C. Stachniess, "Predictive exploration considering previously mapped environments," Robotics and Automation, 2015 IEEE International Conference on, IEEE, 2015.
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D. R. Thompson and D. Wettergreen, "Intelligent maps for autonomous kilometer-scale science survey," 2008.
The use of science policies to modify path and sampling rate is presented for a static measurement target (topography). Monte Carlo and gradient descent are employedto establish so-called hyperparamters to define the sampling distribution.
J. Vallvé and J. Andrade-Cetto, “Dense entropy decrease estimation for mobile robot exploration,” in Proceedings - IEEE International Conference on Robotics and Automation, 2014.
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J. Vallvé and J. Andrade-Cetto, "Potential information fields for mobile robot exploration," Robotics and Autonomous Systems, vol. 69, pp. 68-79, 2015.
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