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This work presents a modular and hierarchical approach to learn policies for exploring 3D environments, called `Active Neural SLAM'.
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Probabilistic robotics
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Evaluating the efficiency of frontier-based exploration strategies
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KinectFusion: real-time 3D reconstruction and interaction using a moving depth camera
Shahram Izadi, David Kim, Otmar Hilliges, David Molyneaux, Richard Newcombe, Pushmeet Kohli, Jamie Shotton, Steve Hodges, Dustin Freeman, Andrew Davison, and Andrew Fitzgibbon · 2011
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A flexible and scalable slam system with full 3d motion estimation
S. Kohlbrecher, J. Meyer, O. von Stryk, and U. Klingauf · 2011
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Dtam: Dense tracking and mapping in real-time
Richard A Newcombe, Steven J Lovegrove, and Andrew J Davison · 2011
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Large-scale semantic mapping and reasoning with heterogeneous modalities
Andrzej Pronobis and Patric Jensfelt · 2012
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A frontier-void-based approach for autonomous exploration in 3d
Christian Dornhege and Alexander Kleiner · 2013
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Learning semantic maps from natural language descriptions
Matthew R Walter, Sachithra Hemachandra, Bianca Homberg, Stefanie Tellex, and Seth Teller · 2013
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Active slam and exploration with particle filters using kullback-leibler divergence
Luca Carlone, Jingjing Du, Miguel Kaouk Ng, Basilio Bona, and Marina Indri · 2014
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On the properties of neural machine translation: Encoder-decoder approaches
Kyunghyun Cho, Bart Van Merriënboer, Dzmitry Bahdanau, and Yoshua Bengio · 2014
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Visual simultaneous localization and mapping: a survey
Autonomous reconstruction of unknown indoor scenes guided by time-varying tensor fields
Kai Xu, Lintao Zheng, Zihao Yan, Guohang Yan, Eugene Zhang, Matthias Niessner, Oliver Deussen, Daniel Cohen-Or, and Hui Huang · 2017
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Neural slam: Learning to explore with external memory
Jingwei Zhang, Lei Tai, Joschka Boedecker, Wolfram Burgard, and Ming Liu · 2017
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Target-driven visual navigation in indoor scenes using deep reinforcement learning
Yuke Zhu, Roozbeh Mottaghi, Eric Kolve, Joseph J Lim, Abhinav Gupta, Li Fei-Fei, and Ali Farhadi · 2017
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On evaluation of embodied navigation agents
Peter Anderson, Angel Chang, Devendra Singh Chaplot, Alexey Dosovitskiy, Saurabh Gupta, Vladlen Koltun, Jana Kosecka, Jitendra Malik, Roozbeh Mottaghi, Manolis Savva, et al · 2018
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Active neural localization
Devendra Singh Chaplot, Emilio Parisotto, and Ruslan Salakhutdinov · 2018
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J. Fuentes-Pacheco, J. Ruiz-Ascencio, and J. M. Rendón-Mancha · 2015
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Max Jaderberg, Karen Simonyan, Andrew Zisserman, et al · 2015
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Transfer deep reinforcement learning in 3d environments: An empirical study
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Mapnet: An allocentric spatial memory for mapping environments
Joao F Henriques and Andrea Vedaldi · 2018
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Pytorch implementations of reinforcement learning algorithms
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Gated path planning networks
Lisa Lee, Emilio Parisotto, Devendra Singh Chaplot, Eric Xing, and Ruslan Salakhutdinov · 2018
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Neural map: Structured memory for deep reinforcement learning
Emilio Parisotto and Ruslan Salakhutdinov · 2018
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Semi-parametric topological memory for navigation
Nikolay Savinov, Alexey Dosovitskiy, and Vladlen Koltun · 2018
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Reinforcement learning: An introduction
Richard S Sutton and Andrew G Barto · 2018
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Gibson Env: real-world perception for embodied agents
Fei Xia, Amir R. Zamir, Zhi-Yang He, Alexander Sax, Jitendra Malik, and Silvio Savarese · 2018
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Combining optimal control and learning for visual navigation in novel environments
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Learning exploration policies for navigation
Tao Chen, Saurabh Gupta, and Abhinav Gupta · 2019
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Scene memory transformer for embodied agents in long-horizon tasks
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Episodic curiosity through reachability
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Habitat: A platform for embodied ai research
Manolis Savva, Abhishek Kadian, Oleksandr Maksymets, Yili Zhao, Erik Wijmans, Bhavana Jain, Julian Straub, Jia Liu, Vladlen Koltun, Jitendra Malik, et al · 2019
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