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The ability to autonomously explore and navigate a physical space is a fundamental requirement for virtually any mobile autonomous agent, from household robotic vacuums to autonomous vehicles.
The complexity of robot motion planning
John Canny · 1988
Earlier work this paper cites.
A robot exploration and mapping strategy based on a semantic hierarchy of spatial representations
Benjamin Kuipers and Yung-Tai Byun · 1991
Earlier work this paper cites.
Probabilistic roadmaps for path planning in high-dimensional configuration spaces
Lydia E Kavraki, Petr Svestka, J-C Latombe, and Mark H Overmars · 1996
Earlier work this paper cites.
A frontier-based approach for autonomous exploration
Brian Yamauchi · 1997
Earlier work this paper cites.
Motion planning in dynamic environments using velocity obstacles
Paolo Fiorini and Zvi Shiller · 1998
Earlier work this paper cites.
Rapidly-exploring random trees: A new tool for path planning
Steven M LaValle · 1998
Earlier work this paper cites.
Probabilistic robotics
Sebastian Thrun, Wolfram Burgard, and Dieter Fox · 2005
Earlier work this paper cites.
Active slam in structured environments
Cindy Leung, Shoudong Huang, and Gamini Dissanayake · 2008
Earlier work this paper cites.
Learning long-range vision for autonomous off-road driving
Raia Hadsell, Pierre Sermanet, Jan Ben, Ayse Erkan, Marco Scoffier, Koray Kavukcuoglu, Urs Muller, and Yann LeCun · 2009
Earlier work this paper cites.
A frontier-void-based approach for autonomous exploration in 3d
Christian Dornhege and Alexander Kleiner · 2013
Earlier work this paper cites.
Microsoft coco: Common objects in context
Tsung-Yi Lin, Michael Maire, Serge Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C Lawrence Zitnick · 2014
Earlier work this paper cites.
U-net: Convolutional networks for biomedical image segmentation
Olaf Ronneberger, Philipp Fischer, and Thomas Brox · 2015
Earlier work this paper cites.
Playing doom with slam-augmented deep reinforcement learning
Shehroze Bhatti, Alban Desmaison, Ondrej Miksik, Nantas Nardelli, N Siddharth, and Philip HS Torr · 2016
Earlier work this paper cites.
Past, present, and future of simultaneous localization and mapping: Toward the robust-perception age
Cesar Cadena, Luca Carlone, Henry Carrillo, Yasir Latif, Davide Scaramuzza, José Neira, Ian Reid, and John J Leonard · 2016
Earlier work this paper cites.
The cityscapes dataset for semantic urban scene understanding
Marius Cordts, Mohamed Omran, Sebastian Ramos, Timo Rehfeld, Markus Enzweiler, Rodrigo Benenson, Uwe Franke, Stefan Roth, and Bernt Schiele · 2016
Earlier work this paper cites.
Autonomous vehicles: disengagements, accidents and reaction times
Vinayak V Dixit, Sai Chand, and Divya J Nair · 2016
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Socially compliant mobile robot navigation via inverse reinforcement learning
Henrik Kretzschmar, Markus Spies, Christoph Sprunk, and Wolfram Burgard · 2016
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A survey of motion planning and control techniques for self-driving urban vehicles
Brian Paden, Michal Čáp, Sze Zheng Yong, Dmitry Yershov, and Emilio Frazzoli · 2016
Cited alongside, same era.
Supersizing self-supervision: Learning to grasp from 50k tries and 700 robot hours
Lerrel Pinto and Abhinav Gupta · 2016
Cited alongside, same era.
Oblige level maker
Andrew Apted · 2017
Dynaslam: Tracking, mapping, and inpainting in dynamic scenes
Berta Bescos, José M Fácil, Javier Civera, and José Neira · 2018
Later among the works it cites.
Mark yourself: Road marking segmentation via weakly-supervised annotations from multimodal data
Tom Bruls, Will Maddern, Akshay A Morye, and Paul Newman · 2018
Later among the works it cites.
Changan Chen, Yuejiang Liu, Sven Kreiss, and Alexandre Alahi · 2018
Later among the works it cites.
Beauty and the beast: Optimal methods meet learning for drone racing
Elia Kaufmann, Mathias Gehrig, Philipp Foehn, René Ranftl, Alexey Dosovitskiy, Vladlen Koltun, and Davide Scaramuzza · 2018
Later among the works it cites.
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Probabilistic data association for semantic slam
Sean Bowman, Nikolay Atanasov, Kostas Daniilidis, and George Pappas · 2017
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Learning to fly by crashing
Dhiraj Gandhi, Lerrel Pinto, and Abhinav Gupta · 2017
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Cognitive mapping and planning for visual navigation
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Cited alongside, same era.
Semanticfusion: Dense 3d semantic mapping with convolutional neural networks
John McCormac, Ankur Handa, Andrew Davison, and Stefan Leutenegger · 2017
Cited alongside, same era.
Learning to navigate in complex environments
Piotr Mirowski, Razvan Pascanu, Fabio Viola, Hubert Soyer, Andy Ballard, Andrea Banino, Misha Denil, Ross Goroshin, Laurent Sifre, Koray Kavukcuoglu, et al · 2017
Cited alongside, same era.
MINOS: Multimodal indoor simulator for navigation in complex environments
Manolis Savva, Angel X. Chang, Alexey Dosovitskiy, Thomas Funkhouser, and Vladlen Koltun · 2017
Cited alongside, same era.
Atanas Mirchev, Baris Kayalibay, Patrick van der Smagt, and Justin Bayer · 2018
Later among the works it cites.
Driving policy transfer via modularity and abstraction
Matthias Müller, Alexey Dosovitskiy, Bernard Ghanem, and Vladen Koltun · 2018
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Semi-parametric topological memory for navigation
Nikolay Savinov, Alexey Dosovitskiy, and Vladlen Koltun · 2018
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Building generalizable agents with a realistic and rich 3d environment
Yi Wu, Yuxin Wu, Georgia Gkioxari, and Yuandong Tian · 2018
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Vizdoom competitions: Playing doom from pixels
Marek Wydmuch, Michał Kempka, and Wojciech Jaśkowski · 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
Somil Bansal, Varun Tolani, Saurabh Gupta, Jitendra Malik, and Claire Tomlin · 2019
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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
Kuan Fang, Alexander Toshev, Li Fei-Fei, and Silvio Savarese · 2019
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Learned map prediction for enhanced mobile robot exploration
Rakesh Shrestha, Fei-Peng Tian, Wei Feng, Ping Tan, and Richard Vaughan · 2019
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