Collision Avoidance in Pedestrian-Rich Environments With Deep Reinforcement Learning
暂无分享,去创建一个
[1] Wolfram Burgard,et al. Socially compliant mobile robot navigation via inverse reinforcement learning , 2016, Int. J. Robotics Res..
[2] Jonathan P. How,et al. Socially aware motion planning with deep reinforcement learning , 2017, 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
[3] Hannes Sommer,et al. Predicting actions to act predictably: Cooperative partial motion planning with maximum entropy models , 2016, 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
[4] Silvio Savarese,et al. Social LSTM: Human Trajectory Prediction in Crowded Spaces , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[5] James B. Rawlings,et al. Tutorial overview of model predictive control , 2000 .
[6] Dinesh Manocha,et al. Reciprocal n-Body Collision Avoidance , 2011, ISRR.
[7] Jonathan P. How,et al. Dynamic Clustering via Asymptotics of the Dependent Dirichlet Process Mixture , 2013, NIPS.
[8] Wolfram Burgard,et al. The dynamic window approach to collision avoidance , 1997, IEEE Robotics Autom. Mag..
[9] Alec Radford,et al. Proximal Policy Optimization Algorithms , 2017, ArXiv.
[10] Stephen Tyree,et al. Reinforcement Learning through Asynchronous Advantage Actor-Critic on a GPU , 2016, ICLR.
[11] Hao Zhang,et al. Towards Optimally Decentralized Multi-Robot Collision Avoidance via Deep Reinforcement Learning , 2017, 2018 IEEE International Conference on Robotics and Automation (ICRA).
[12] Jonathan P. How,et al. Probabilistically safe motion planning to avoid dynamic obstacles with uncertain motion patterns , 2013, Auton. Robots.
[13] Gonzalo Ferrer,et al. Social-aware robot navigation in urban environments , 2013, 2013 European Conference on Mobile Robots.
[14] Wolfram Burgard,et al. A navigation system for robots operating in crowded urban environments , 2013, 2013 IEEE International Conference on Robotics and Automation.
[15] Eduardo F. Morales,et al. An Introduction to Reinforcement Learning , 2011 .
[16] Jürgen Schmidhuber,et al. Long Short-Term Memory , 1997, Neural Computation.
[17] Jonathan P. How,et al. Crossmodal Attentive Skill Learner , 2017, AAMAS.
[18] Quoc V. Le,et al. Sequence to Sequence Learning with Neural Networks , 2014, NIPS.
[19] Andreas Krause,et al. Robot navigation in dense human crowds: the case for cooperation , 2013, 2013 IEEE International Conference on Robotics and Automation.
[20] Joelle Pineau,et al. Socially Adaptive Path Planning in Human Environments Using Inverse Reinforcement Learning , 2016, Int. J. Soc. Robotics.
[21] Yoshua Bengio,et al. Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation , 2014, EMNLP.
[22] Maxim Likhachev,et al. SIPP: Safe interval path planning for dynamic environments , 2011, 2011 IEEE International Conference on Robotics and Automation.
[23] Alex Graves,et al. Asynchronous Methods for Deep Reinforcement Learning , 2016, ICML.
[24] Herke van Hoof,et al. Addressing Function Approximation Error in Actor-Critic Methods , 2018, ICML.
[25] Ming Liu,et al. Virtual-to-real deep reinforcement learning: Continuous control of mobile robots for mapless navigation , 2017, 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
[26] Michael Everett,et al. Robot designed for socially acceptable navigation , 2017 .
[27] Andreas Krause,et al. Unfreezing the robot: Navigation in dense, interacting crowds , 2010, 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems.
[28] Р Ю Чуйков,et al. Обнаружение транспортных средств на изображениях загородных шоссе на основе метода Single shot multibox Detector , 2017 .
[29] Wei Liu,et al. SSD: Single Shot MultiBox Detector , 2015, ECCV.
[30] Jimmy Ba,et al. Adam: A Method for Stochastic Optimization , 2014, ICLR.
[31] Wolfram Burgard,et al. Feature-Based Prediction of Trajectories for Socially Compliant Navigation , 2012, Robotics: Science and Systems.
[32] Xin Zhang,et al. End to End Learning for Self-Driving Cars , 2016, ArXiv.
[33] Jonathan P. How,et al. MAR-CPS: Measurable Augmented Reality for Prototyping Cyber-Physical Systems , 2015 .
[34] Tom Schaul,et al. Rainbow: Combining Improvements in Deep Reinforcement Learning , 2017, AAAI.
[35] Hiroaki Kitano,et al. RoboCup: The Robot World Cup Initiative , 1997, AGENTS '97.
[36] Jonathan P. How,et al. Decentralized non-communicating multiagent collision avoidance with deep reinforcement learning , 2016, 2017 IEEE International Conference on Robotics and Automation (ICRA).
[37] Igor Mordatch,et al. Emergent Tool Use From Multi-Agent Autocurricula , 2019, ICLR.
[38] Dinesh Manocha,et al. The Hybrid Reciprocal Velocity Obstacle , 2011, IEEE Transactions on Robotics.
[39] Rajeev J. Surati,et al. Measurable Augmented Reality for Prototyping Cyber-Physical Systems , 2018 .
[40] Shane Legg,et al. Human-level control through deep reinforcement learning , 2015, Nature.
[41] Jonathan P. How,et al. Dynamic arrival rate estimation for campus Mobility On Demand network graphs , 2016, 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
[42] Yuan Yu,et al. TensorFlow: A system for large-scale machine learning , 2016, OSDI.
[43] Jonathan P. How,et al. Motion Planning Among Dynamic, Decision-Making Agents with Deep Reinforcement Learning , 2018, 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
[44] Paul A. Beardsley,et al. Optimal Reciprocal Collision Avoidance for Multiple Non-Holonomic Robots , 2010, DARS.
[45] Javier García,et al. A comprehensive survey on safe reinforcement learning , 2015, J. Mach. Learn. Res..