Planning for robotic exploration based on forward simulation
暂无分享,去创建一个
[1] Alberto Quattrini Li,et al. A semantically-informed multirobot system for exploration of relevant areas in search and rescue settings , 2016, Auton. Robots.
[2] Frank Dellaert,et al. Planning in the continuous domain: A generalized belief space approach for autonomous navigation in unknown environments , 2015, Int. J. Robotics Res..
[3] Cyrill Stachniss,et al. Predictive exploration considering previously mapped environments , 2015, 2015 IEEE International Conference on Robotics and Automation (ICRA).
[4] Risto Ritala,et al. Optimal sensing via multi-armed bandit relaxations in mixed observability domains , 2015, 2015 IEEE International Conference on Robotics and Automation (ICRA).
[5] Frank Dellaert,et al. Planning under uncertainty in the continuous domain: A generalized belief space approach , 2014, 2014 IEEE International Conference on Robotics and Automation (ICRA).
[6] George J. Pappas,et al. Information acquisition with sensing robots: Algorithms and error bounds , 2013, 2014 IEEE International Conference on Robotics and Automation (ICRA).
[7] Alkis Gotovos,et al. Fully autonomous focused exploration for robotic environmental monitoring , 2014, 2014 IEEE International Conference on Robotics and Automation (ICRA).
[8] Vijay Kumar,et al. Approximate representations for multi-robot control policies that maximize mutual information , 2014, Robotics: Science and Systems.
[9] Wolfram Burgard,et al. Lifelong localization in changing environments , 2013, Int. J. Robotics Res..
[10] Wolfram Burgard,et al. Occupancy Grid Models for Robot Mapping in Changing Environments , 2012, AAAI.
[11] Arturo Gil,et al. A comparison of path planning strategies for autonomous exploration and mapping of unknown environments , 2012, Auton. Robots.
[12] Simon M. Lucas,et al. A Survey of Monte Carlo Tree Search Methods , 2012, IEEE Transactions on Computational Intelligence and AI in Games.
[13] Joel Veness,et al. Monte-Carlo Planning in Large POMDPs , 2010, NIPS.
[14] Olivier Buffet,et al. A POMDP Extension with Belief-dependent Rewards , 2010, NIPS.
[15] Jingjing Du,et al. An application of Kullback-Leibler divergence to active SLAM and exploration with Particle Filters , 2010, 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems.
[16] Vincenzo Caglioti,et al. An information-based exploration strategy for environment mapping with mobile robots , 2010, Robotics Auton. Syst..
[17] Pedro U. Lima,et al. A Decision-Theoretic Approach to Dynamic Sensor Selection in Camera Networks , 2009, ICAPS.
[18] Nando de Freitas,et al. A Bayesian exploration-exploitation approach for optimal online sensing and planning with a visually guided mobile robot , 2009, Auton. Robots.
[19] J. Maciejowski,et al. Sequential Monte Carlo for Model Predictive Control , 2009 .
[20] Morgan Quigley,et al. ROS: an open-source Robot Operating System , 2009, ICRA 2009.
[21] Alfred O. Hero,et al. Partially Observable Markov Decision Process Approximations for Adaptive Sensing , 2009, Discret. Event Dyn. Syst..
[22] Richard Vaughan,et al. Massively multi-robot simulation in stage , 2008, Swarm Intelligence.
[23] David Hsu,et al. SARSOP: Efficient Point-Based POMDP Planning by Approximating Optimally Reachable Belief Spaces , 2008, Robotics: Science and Systems.
[24] Andreas Krause,et al. Near-Optimal Sensor Placements in Gaussian Processes: Theory, Efficient Algorithms and Empirical Studies , 2008, J. Mach. Learn. Res..
[25] Francesco Amigoni,et al. Experimental evaluation of some exploration strategies for mobile robots , 2008, 2008 IEEE International Conference on Robotics and Automation.
[26] Joelle Pineau,et al. Online Planning Algorithms for POMDPs , 2008, J. Artif. Intell. Res..
[27] Wolfram Burgard,et al. Efficient exploration of unknown indoor environments using a team of mobile robots , 2008, Annals of Mathematics and Artificial Intelligence.
[28] Arnaud Doucet,et al. Particle methods for maximum likelihood estimation in latent variable models , 2008, Stat. Comput..
[29] Nicholas Roy,et al. Trajectory Optimization using Reinforcement Learning for Map Exploration , 2008, Int. J. Robotics Res..
[30] Javier González,et al. A Novel Measure of Uncertainty for Mobile Robot SLAM with Rao—Blackwellized Particle Filters , 2008, Int. J. Robotics Res..
[31] Martial Hebert,et al. Extending the Path-Planning Horizon , 2007, Int. J. Robotics Res..
[32] Vikram Krishnamurthy,et al. Structured Threshold Policies for Dynamic Sensor Scheduling—A Partially Observed Markov Decision Process Approach , 2007, IEEE Transactions on Signal Processing.
[33] Wolfram Burgard,et al. Improved Techniques for Grid Mapping With Rao-Blackwellized Particle Filters , 2007, IEEE Transactions on Robotics.
[34] Csaba Szepesvári,et al. Bandit Based Monte-Carlo Planning , 2006, ECML.
[35] Joelle Pineau,et al. Anytime Point-Based Approximations for Large POMDPs , 2006, J. Artif. Intell. Res..
[36] Hugh F. Durrant-Whyte,et al. Simultaneous localization and mapping: part I , 2006, IEEE Robotics & Automation Magazine.
[37] Rafael Murrieta-Cid,et al. Planning exploration strategies for simultaneous localization and mapping , 2006, Robotics Auton. Syst..
[38] Thomas M. Cover,et al. Elements of information theory (2. ed.) , 2006 .
[39] Hugh Durrant-Whyte,et al. Simultaneous Localisation and Mapping ( SLAM ) : Part I The Essential Algorithms , 2006 .
[40] K. Kastella,et al. A Comparison of Task Driven and Information Driven Sensor Management for Target Tracking , 2005, Proceedings of the 44th IEEE Conference on Decision and Control.
[41] Nikos A. Vlassis,et al. Perseus: Randomized Point-based Value Iteration for POMDPs , 2005, J. Artif. Intell. Res..
[42] Wolfram Burgard,et al. Information Gain-based Exploration Using Rao-Blackwellized Particle Filters , 2005, Robotics: Science and Systems.
[43] Gamini Dissanayake,et al. Multi-Step Look-Ahead Trajectory Planning in SLAM: Possibility and Necessity , 2005, Proceedings of the 2005 IEEE International Conference on Robotics and Automation.
[44] Nicholas Roy,et al. Global A-Optimal Robot Exploration in SLAM , 2005, Proceedings of the 2005 IEEE International Conference on Robotics and Automation.
[45] Dimitri P. Bertsekas,et al. Dynamic Programming and Suboptimal Control: A Survey from ADP to MPC , 2005, Eur. J. Control.
[46] Sean R Eddy,et al. What is dynamic programming? , 2004, Nature Biotechnology.
[47] Peter Auer,et al. Finite-time Analysis of the Multiarmed Bandit Problem , 2002, Machine Learning.
[48] Christian P. Robert,et al. Monte Carlo Statistical Methods , 2005, Springer Texts in Statistics.
[49] P. Moral,et al. Sequential Monte Carlo samplers , 2002, cond-mat/0212648.
[50] Alexei Makarenko,et al. Information based adaptive robotic exploration , 2002, IEEE/RSJ International Conference on Intelligent Robots and Systems.
[51] Héctor H. González-Baños,et al. Navigation Strategies for Exploring Indoor Environments , 2002, Int. J. Robotics Res..
[52] Jan M. Maciejowski,et al. Predictive control : with constraints , 2002 .
[53] Sebastian Thrun,et al. Probabilistic robotics , 2002, CACM.
[54] Robert Givan,et al. A framework for simulation-based network control via hindsight optimization , 2000, Proceedings of the 39th IEEE Conference on Decision and Control (Cat. No.00CH37187).
[55] Milos Hauskrecht,et al. Value-Function Approximations for Partially Observable Markov Decision Processes , 2000, J. Artif. Intell. Res..
[56] Leslie Pack Kaelbling,et al. Planning and Acting in Partially Observable Stochastic Domains , 1998, Artif. Intell..
[57] Brian Yamauchi,et al. A frontier-based approach for autonomous exploration , 1997, Proceedings 1997 IEEE International Symposium on Computational Intelligence in Robotics and Automation CIRA'97. 'Towards New Computational Principles for Robotics and Automation'.
[58] Ieee Robotics. Proceedings 1997 IEEE International Symposium on Computational Intelligence in Robotics and Automation CIRA'97 - Towards New Computational Principles for Robotics and Automation, July 10-11, 1997, Monterey, California, USA , 1997, CIRA.
[59] Jun S. Liu,et al. Sequential Monte Carlo methods for dynamic systems , 1997 .
[60] Dimitri P. Bertsekas,et al. Dynamic Programming and Optimal Control, Two Volume Set , 1995 .
[61] Martin L. Puterman,et al. Markov Decision Processes: Discrete Stochastic Dynamic Programming , 1994 .
[62] Thomas M. Cover,et al. Elements of Information Theory , 2005 .
[63] Hans P. Moravec. Sensor Fusion in Certainty Grids for Mobile Robots , 1988, AI Mag..
[64] John N. Tsitsiklis,et al. The Complexity of Markov Decision Processes , 1987, Math. Oper. Res..
[65] Edward J. Sondik,et al. The Optimal Control of Partially Observable Markov Processes over a Finite Horizon , 1973, Oper. Res..
[66] M. Degroot. Optimal Statistical Decisions , 1970 .
[67] Karl Johan Åström,et al. Optimal control of Markov processes with incomplete state information , 1965 .
[68] Chih-Han Yu. Open-loop plans in multi-robot POMDPs , 2022 .