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Finding feasible, collision-free paths for multiagent systems can be challenging, particularly in non-communicating scenarios where each agent's intent (e.g.
F. Augugliaro, A. P. Schoellig, and R. D’Andrea, “Generation of collision-free trajectories for a quadrocopter fleet: A sequential convex programming approach,” in 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems , Oct. 2012, pp. 1917–1922
1922
Earlier work this paper cites.
J. Van den Berg, M. Lin, and D. Manocha, “Reciprocal velocity obstacles for real-time multi-agent navigation,” in Proceedings of the 2008 IEEE International Conference on Robotics and Automation (ICRA) , 2008, pp. 1928–1935
1935
Earlier work this paper cites.
R. S. Sutton and A. G. Barto, Introduction to Reinforcement Learning , 1st ed. Cambridge, MA, USA: MIT Press, 1998
1998
Earlier work this paper cites.
O. Purwin, R. D’Andrea, and J.-W. Lee, “Theory and implementation of path planning by negotiation for decentralized agents,” Robotics and Autonomous Systems , vol. 56, no. 5, pp. 422–436, May 2008
2008
Earlier work this paper cites.
S. J. Guy, J. Chhugani, C. Kim, N. Satish, M. Lin, D. Manocha, and P. Dubey, “ClearPath: Highly parallel collision avoidance for multi-agent simulation,” in Proceedings of the 2009 ACM SIGGRAPH/Eurographics Symposium on Computer Animation , ser. SCA ’09. New York, NY, USA: ACM, 2009, pp. 177–187
2009
Earlier work this paper cites.
P. Trautman and A. Krause, “Unfreezing the robot: Navigation in dense, interacting crowds,” in 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) , Oct. 2010, pp. 797–803
2010
Earlier work this paper cites.
V. R. Desaraju and J. P. How, “Decentralized path planning for multi-agent teams in complex environments using rapidly-exploring random trees,” in 2011 IEEE International Conference on Robotics and Automation (ICRA) , May 2011, pp. 4956–4961
2011
Earlier work this paper cites.
J. Snape, J. Van den Berg, S. J. Guy, and D. Manocha, “The hybrid reciprocal velocity obstacle,” IEEE Transactions on Robotics , vol. 27, no. 4, pp. 696–706, Aug. 2011
2011
Earlier work this paper cites.
J. Van den Berg, S. J. Guy, M. Lin, and D. Manocha, “Reciprocal n-body collision avoidance,” in Robotics Research , ser. Springer Tracts in Advanced Robotics. Springer Berlin Heidelberg, 2011, no. 70, pp. 3–19
2011
Cited alongside, same era.
M. Phillips and M. Likhachev, “SIPP: Safe interval path planning for dynamic environments,” in 2011 IEEE International Conference on Robotics and Automation (ICRA) , May 2011, pp. 5628–5635
2011
Cited alongside, same era.
D. Mellinger, A. Kushleyev, and V. Kumar, “Mixed-integer quadratic program trajectory generation for heterogeneous quadrotor teams,” in 2012 IEEE International Conference on Robotics and Automation (ICRA) , May 2012, pp. 477–483
2012
Cited alongside, same era.
M. Kuderer, H. Kretzschmar, C. Sprunk, and W. Burgard, “Feature-based prediction of trajectories for socially compliant navigation,” in Robotics:Science and Systems , 2012
2012
Cited alongside, same era.
A. Bera and D. Manocha, “Realtime multilevel crowd tracking using reciprocal velocity obstacles,” in 2014 22nd International Conference on Pattern Recognition (ICPR) , Aug. 2014, pp. 4164–4169
2014
Later among the works it cites.
S. Kim, S. J. Guy, W. Liu, D. Wilkie, R. W. Lau, M. C. Lin, and D. Manocha, “BRVO: predicting pedestrian trajectories using velocity-space reasoning,” The International Journal of Robotics Research , vol. 34, no. 2, pp. 201–217, Feb. 2015
2015
Later among the works it cites.
Y. Chen, M. Cutler, and J. P. How, “Decoupled multiagent path planning via incremental sequential convex programming,” in proceedings of the 2015 IEEE International Conference on Robotics and Automation (ICRA) , May 2015, pp. 5954–5961
2015
Later among the works it cites.
V. Mnih, K. Kavukcuoglu, D. Silver, A. A. Rusu, J. Veness, M. G. Bellemare, A. Graves, M. Riedmiller, A. K. Fidjeland, G. Ostrovski, S. Petersen, C. Beattie, A. Sadik, I. Antonoglou, H. King, D. Kumaran, D. Wierstra, S. Legg, and D. Hassabis, “Human-level control through deep reinforcement learning,” Nature , vol. 518, no. 7540, pp. 529–533, Feb. 2015
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G. Ferrer, A. Garrell, and A. Sanfeliu, “Social-aware robot navigation in urban environments,” in 2013 European Conference on Mobile Robots (ECMR) , Sept. 2013, pp. 331–336
2013
Cited alongside, same era.
G. S. Aoude, B. D. Luders, J. M. Joseph, N. Roy, and J. P. How, “Probabilistically safe motion planning to avoid dynamic obstacles with uncertain motion patterns,” Autonomous Robots , vol. 35, no. 1, pp. 51–76, May 2013
2013
Cited alongside, same era.
P. Trautman, J. Ma, R. M. Murray, and A. Krause, “Robot navigation in dense human crowds: the case for cooperation,” in Proceedings of the 2013 IEEE International Conference on Robotics and Automation (ICRA) , May 2013, pp. 2153–2160
2013
Cited alongside, same era.
S. Choi, E. Kim, and S. Oh, “Real-time navigation in crowded dynamic environments using Gaussian process motion control,” in 2014 IEEE International Conference on Robotics and Automation (ICRA) , May 2014, pp. 3221–3226
2014
Cited alongside, same era.
2015
Later among the works it cites.
H. Kretzschmar, M. Spies, C. Sprunk, and W. Burgard, “Socially compliant mobile robot navigation via inverse reinforcement learning,” The International Journal of Robotics Research , Jan. 2016
2016
Closest in time.
D. Silver, A. Huang, C. J. Maddison, A. Guez, L. Sifre, G. van den Driessche, J. Schrittwieser, I. Antonoglou, V. Panneershelvam, M. Lanctot, S. Dieleman, D. Grewe, J. Nham, N. Kalchbrenner, I. Sutskever, T. Lillicrap, M. Leach, K. Kavukcuoglu, T. Graepel, and D. Hassabis, “Mastering the game of Go with deep neural networks and tree search,” Nature , vol. 529, no. 7587, pp. 484–489, Jan. 2016
2016
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M. Zhang, Z. McCarthy, C. Finn, S. Levine, and P. Abbeel, “Learning deep neural network policies with continuous memory states,” in 2016 IEEE International Conference on Robotics and Automation (ICRA) , May 2016, pp. 520–527
2016
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