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Forecasting the behavior of other agents is an integral part of the modern robotic autonomy stack, especially in safety-critical scenarios with human-robot interaction, such as autonomous driving.
Comparison of similarity measures for trajectory clustering in outdoor surveillance scenes
Z. Zhang, K. Huang, and T. Tan · 2006
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A simple unicycle
S. M. LaValle · 2006
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A survey of vision-based trajectory learning and analysis for surveillance
B. T. Morris and M. M. Trivedi · 2008
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Sampling-based algorithms for optimal motion planning
S. Karaman and E. Frazzoli · 2011
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S. Levine and V. Koltun · 2012
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Human-aware robot navigation: A survey
T. Kruse, A. K. Pandey, R. Alami, and A. Kirsch · 2013
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A survey on motion prediction and risk assessment for intelligent vehicles
S. Lefèvre, D. Vasquez, and C. Laugier · 2014
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Y. Zheng · 2015
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Fast Marching Tree: a fast marching sampling-based method for optimal motion planning in many dimensions
L. Janson, E. Schmerling, A. Clark, and M. Pavone · 2015
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Comparison and evaluation of pedestrian motion models for vehicle safety systems
N. Brouwer, H. Kloeden, and C. Stiller · 2016
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A review of social-aware navigation frameworks for service robot in dynamic human environments
S. F. Chik, C. F. Yeong, E. L. M. Su, T. Y. Lim, Y. Subramaniam, and P. J. H. Chin · 2016
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A survey of motion planning and control techniques for self-driving urban vehicles
B. Paden, M. Čáp, S. Z. Yong, D. Yershov, and E. Frazzoli · 2016
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A survey of methods for safe human-robot interaction
P. A. Lasota, T. Fong, and J. A. Shah · 2017
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Group and Crowd Behavior for Computer Vision
V. Murino, M. Cristani, S. Shah, and S. Savarese · 2017
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How good is my prediction? finding a similarity measure for trajectory prediction evaluation
J. Quehl, H. Hu, O. Taş, E. Rehder, and M. Lauer · 2017
Cited alongside, same era.
Towards a rigorous science of interpretable machine learning
F. Doshi-Velez and B. Kim · 2017
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Automatic differentiation in PyTorch
A. Paszke, S. Gross, S. Chintala, G. Chanan, E. Yang, Z. DeVito, Z. Lin, A. Desmaison, L. Antiga, and A. Lerer · 2017
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Survey on vision-based path prediction
T. Hirakawa, T. Yamashita, T. Tamaki, and H. Fujiyoshi · 2018
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Self-driving safety report, 2018
General Motors · 2018
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Fast and furious: Real time end-to-end 3d detection, tracking and motion forecasting with a single convolutional net
Risk-sensitive sequential action control with multi-modal human trajectory forecasting for safe crowd-robot interaction
H. Nishimura, B. Ivanovic, A. Gaidon, M. Pavone, and M. Schwager · 2020
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MATS: An interpretable trajectory forecasting representation for planning and control
B. Ivanovic, A. Elhafsi, G. Rosman, A. Gaidon, and M. Pavone · 2020
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Learning to evaluate perception models using planner-centric metrics
J. Philion, A. Kar, and S. Fidler · 2020
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One thousand and one hours: Self-driving motion prediction dataset
J. Houston, G. Zuidhof, L. Bergamini, Y. Ye, A. Jain, S. Omari, V. Iglovikov, and P. Ondruska · 2020
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Scalability in perception for autonomous driving: Waymo open dataset
P. Sun, H. Kretzschmar, X. Dotiwalla, A. Chouard, V. Patnaik, P. Tsui, J. Guo, Y. Zhou, Y. Chai, B. Caine, V. Vasudevan, W. Han, J. Ngiam, H. Zhao, A. Timofeev, S. Ettinger, M. Krivokon, A. Gao, A. Joshi, S. Zhao, S. Cheng, Y. Zhang, J. Shlens, Z. Chen, and D. Anguelov · 2020
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W. Luo, B. Yang, and R. Urtasun · 2018
Cited alongside, same era.
Multimodal probabilistic model-based planning for human-robot interaction
E. Schmerling, K. Leung, W. Vollprecht, and M. Pavone · 2018
Cited alongside, same era.
The Trajectron: Probabilistic multi-agent trajectory modeling with dynamic spatiotemporal graphs
B. Ivanovic and M. Pavone · 2019
Cited alongside, same era.
nuScenes: A multimodal dataset for autonomous driving, 2019
H. Caesar, V. Bankiti, A. H. Lang, S. Vora, V. E. Liong, Q. Xu, A. Krishnan, Y. Pan, G. Baldan, and O. Beijbom · 2019
Cited alongside, same era.
Interpretable Machine Learning , chapter 4.1 Linear Regression
C. Molnar · 2019
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A principled approach to safety, 2020
Uber Advanced Technologies Group · 2020
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Self-driving safety report, 2020
Lyft · 2020
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Safety report, 2021
Waymo · 2021
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Developing a self-driving system you can trust, Apr. 2021
Argo AI · 2021
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Voluntary safety self-assessment, 2021
Motional · 2021
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Safety report volume 2.0, 2021
Zoox · 2021
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Self-driving safety report, 2021
NVIDIA · 2021
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Heterogeneous-agent trajectory forecasting incorporating class uncertainty, 2021
B. Ivanovic, K.-H. Lee, P. Tokmakov, B. Wulfe, R. McAllister, A. Gaidon, and M. Pavone · 2021
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Leveraging neural network gradients within trajectory optimization for proactive human-robot interactions
S. Schaefer, K. Leung, B. Ivanovic, and M. Pavone · 2021
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Identifying driver interactions via conditional behavior prediction
E. Tolstaya, R. Mahjourian, C. Downey, B. Varadarajan, B. Sapp, and D. Anguelov · 2021
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Collision avoidance in pedestrian-rich environments with deep reinforcement learning
M. Everett, Y. F. Chen, and J. P. How · 2021
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