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The problem of path planning has been studied for years.
An introduction to splines for use in computer graphics and geometric modeling
Richard H Bartels, John C Beatty, and Brian A Barsky · 1995
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Convolutional networks for images, speech, and time series
Yann LeCun, Yoshua Bengio, et al · 1995
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Cubic spline interpolation
Sky McKinley and Megan Levine · 1998
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Path planning using lazy prm
L Kavraki and R Bohlin · 2000
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Design and use paradigms for gazebo, an open-source multi-robot simulator
Nathan Koenig and Andrew Howard · 2004
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Sampling-based algorithms for optimal motion planning
Sertac Karaman and Emilio Frazzoli · 2011
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End to end learning for self-driving cars
Mariusz Bojarski, Davide Del Testa, Daniel Dworakowski, Bernhard Firner, Beat Flepp, Prasoon Goyal, Lawrence D Jackel, Mathew Monfort, Urs Muller, Jiakai Zhang, et al · 2016
Earlier work this paper cites.
Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Anymal-a highly mobile and dynamic quadrupedal robot
Marco Hutter, Christian Gehring, Dominic Jud, Andreas Lauber, C Dario Bellicoso, Vassilios Tsounis, Jemin Hwangbo, Karen Bodie, Peter Fankhauser, Michael Bloesch, et al · 2016
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Matterport3d: Learning from rgb-d data in indoor environments
Angel Chang, Angela Dai, Thomas Funkhouser, Maciej Halber, Matthias Niessner, Manolis Savva, Shuran Song, Andy Zeng, and Yinda Zhang · 2017
Earlier work this paper cites.
From perception to decision: A data-driven approach to end-to-end motion planning for autonomous ground robots
Mark Pfeiffer, Michael Schaeuble, Juan Nieto, Roland Siegwart, and Cesar Cadena · 2017
Earlier work this paper cites.
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
Cited alongside, same era.
Reinforced imitation: Sample efficient deep reinforcement learning for mapless navigation by leveraging prior demonstrations
Mark Pfeiffer, Samarth Shukla, Matteo Turchetta, Cesar Cadena, Andreas Krause, Roland Siegwart, and Juan Nieto · 2018
Cited alongside, same era.
End-to-end navigation strategy with deep reinforcement learning for mobile robots
Haobin Shi, Lin Shi, Meng Xu, and Kao-Shing Hwang · 2019
Cited alongside, same era.
Dd-ppo: Learning near-perfect pointgoal navigators from 2.5 billion frames
Erik Wijmans, Abhishek Kadian, Ari Morcos, Stefan Lee, Irfan Essa, Devi Parikh, Manolis Savva, and Dhruv Batra · 2019
Cited alongside, same era.
Complementary multi–modal sensor fusion for resilient robot pose estimation in subterranean environments
Learning high-speed flight in the wild
Antonio Loquercio, Elia Kaufmann, René Ranftl, Matthias Müller, Vladlen Koltun, and Davide Scaramuzza · 2021
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Rough terrain navigation for legged robots using reachability planning and template learning
Lorenz Wellhausen and Marco Hutter · 2021
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Real-time optimal navigation planning using learned motion costs
Bowen Yang, Lorenz Wellhausen, Takahiro Miki, Ming Liu, and Marco Hutter · 2021
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Auxiliary tasks and exploration enable objectgoal navigation
Joel Ye, Dhruv Batra, Abhishek Das, and Erik Wijmans · 2021
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High-definition map generation technologies for autonomous driving: a review
Zhibin Bao, Sabir Hossain, Haoxiang Lang, and Xianke Lin · 2022
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Shehryar Khattak, Huan Nguyen, Frank Mascarich, Tung Dang, and Kostas Alexis · 2020
Cited alongside, same era.
Perceive, predict, and plan: Safe motion planning through interpretable semantic representations
Abbas Sadat, Sergio Casas, Mengye Ren, Xinyu Wu, Pranaab Dhawan, and Raquel Urtasun · 2020
Cited alongside, same era.
Falco: Fast likelihood-based collision avoidance with extension to human-guided navigation
Ji Zhang, Chen Hu, Rushat Gupta Chadha, and Sanjiv Singh · 2020
Cited alongside, same era.
Vision-language navigation with self-supervised auxiliary reasoning tasks
Fengda Zhu, Yi Zhu, Xiaojun Chang, and Xiaodan Liang · 2020
Cited alongside, same era.
Learning a state representation and navigation in cluttered and dynamic environments
David Hoeller, Lorenz Wellhausen, Farbod Farshidian, and Marco Hutter · 2021
Cited alongside, same era.
Badgr: An autonomous self-supervised learning-based navigation system
Gregory Kahn, Pieter Abbeel, and Sergey Levine · 2021
Cited alongside, same era.
Investigating bi-level optimization for learning and vision from a unified perspective: A survey and beyond
Risheng Liu, Jiaxin Gao, Jin Zhang, Deyu Meng, and Zhouchen Lin · 2021
Cited alongside, same era.
Autonomous exploration development environment and the planning algorithms
Chao Cao, Hongbiao Zhu, Fan Yang, Yukun Xia, Howie Choset, Jean Oh, and Ji Zhang · 2022
Later among the works it cites.
Learning forward dynamics model and informed trajectory sampler for safe quadruped navigation
Yunho Kim, Chanyoung Kim, and Jemin Hwangbo · 2022
Later among the works it cites.
Gnm: A general navigation model to drive any robot
Dhruv Shah, Ajay Sridhar, Arjun Bhorkar, Noriaki Hirose, and Sergey Levine · 2022
Later among the works it cites.
Learning model predictive controllers with real-time attention for real-world navigation
Xuesu Xiao, Tingnan Zhang, Krzysztof Choromanski, Edward Lee, Anthony Francis, Jake Varley, Stephen Tu, Sumeet Singh, Peng Xu, Fei Xia, et al · 2022
Later among the works it cites.
PyPose: A library for robot learning with physics-based optimization
Chen Wang, Dasong Gao, Kuan Xu, Junyi Geng, Yaoyu Hu, Yuheng Qiu, Bowen Li, Fan Yang, Brady Moon, Abhinav Pandey, Aryan, Jiahe Xu, Tianhao Wu, Haonan He, Daning Huang, Zhongqiang Ren, Shibo Zhao, Taimeng Fu, Pranay Reddy, Xiao Lin, Wenshan Wang, Jingnan Shi, Rajat Talak, Kun Cao, Yi Du, Han Wang, Huai Yu, Shanzhao Wang, Siyu Chen, Ananth Kashyap, Rohan Bandaru, Karthik Dantu, Jiajun Wu, Lihua Xie, Luca Carlone, Marco Hutter, and Sebastian Scherer · 2023
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