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We focus on robot navigation in crowded environments.
Social force model for pedestrian dynamics
D. Helbing and P. Molnár · 1995
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Crowds by example
A. Lerner, Y. Chrysanthou, and D. Lischinski · 2007
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You’ll never walk alone: Modeling social behavior for multi-target tracking
S. Pellegrini, A. Ess, K. Schindler, and L. Van Gool · 2009
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Planning-based prediction for pedestrians
B. D. Ziebart, N. Ratliff, G. Gallagher, C. Mertz, K. Peterson, J. A. Bagnell, M. Hebert, A. K. Dey, and S. Srinivasa · 2009
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Reciprocal n-body collision avoidance
J. van den Berg, S. J. Guy, M. Lin, and D. Manocha · 2011
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Robot navigation in dense human crowds: Statistical models and experimental studies of human-robot cooperation
P. Trautman, J. Ma, R. M. Murray, and A. Krause · 2015
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Socially compliant mobile robot navigation via inverse reinforcement learning
H. Kretzschmar, M. Spies, C. Sprunk, and W. Burgard · 2016
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Egocentric future localization
H. S. Park, J.-J. Hwang, Y. Niu, and J. Shi · 2016
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A point set generation network for 3d object reconstruction from a single image
H. Fan, H. Su, and L. Guibas · 2017
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Red: A simple but effective baseline predictor for the TrajNet benchmark
S. Becker, R. Hug, W. Hübner, and M. Arens · 2018
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Intentnet: Learning to predict intention from raw sensor data
S. Casas, W. Luo, and R. Urtasun · 2018
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Motion prediction of traffic actors for autonomous driving using deep convolutional networks
N. Djuric, V. Radosavljevic, H. Cui, T. Nguyen, F.-C. Chou, T.-H. Lin, and J. G. Schneider · 2018
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Motion planning among dynamic, decision-making agents with deep reinforcement learning
M. Everett, Y. F. Chen, and J. P. How · 2018
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Social GAN: Socially acceptable trajectories with generative adversarial networks
A. Gupta, J. Johnson, L. Fei-Fei, S. Savarese, and A. Alahi · 2018
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Dynamic occupancy grid prediction for urban autonomous driving: A deep learning approach with fully automatic labeling
S. Hoermann, M. Bach, and K. Dietmayer · 2018
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Convolutional neural network for trajectory prediction
N. Nikhil and B. T. Morris · 2018
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Conditional flow variational autoencoders for structured sequence prediction
A. Bhattacharyya, M. Hanselmann, M. Fritz, B. Schiele, and C.-N. Straehle · 2019
Cited alongside, same era.
Crowd-robot interaction: Crowd-aware robot navigation with attention-based deep reinforcement learning
C. Chen, Y. Liu, S. Kreiss, and A. Alahi · 2019
Cited alongside, same era.
Honda P.A.T.H. Bot, 2019
Honda · 2019
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Sophie: An attentive gan for predicting paths compliant to social and physical constraints
Stable balance controller, March 2020
K. Yamane and C. Kurosu · 2020
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Where to go next: Learning a subgoal recommendation policy for navigation in dynamic environments
B. Brito, M. Everett, J. P. How, and J. Alonso-Mora · 2021
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Crowd against the machine: A simulation-based benchmark tool to evaluate and compare robot capabilities to navigate a human crowd
F. Grzeskowiak, D. Gonon, D. Dugas, D. Paez-Granados, J. J. Chung, J. Nieto, R. Siegwart, A. Billard, M. Babel, and J. Pettré · 2021
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From goals, waypoints & paths to long term human trajectory forecasting
K. Mangalam, Y. An, H. Girase, and J. Malik · 2021
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Move Beyond Trajectories: Distribution Space Coupling for Crowd Navigation
M. Sun, F. Baldini, P. Trautman, and T. Murphey · 2021
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A. Sadeghian, V. Kosaraju, A. Sadeghian, N. Hirose, H. Rezatofighi, and S. Savarese · 2019
Cited alongside, same era.
SR-LSTM: State refinement for LSTM towards pedestrian trajectory prediction
P. Zhang, W. Ouyang, P. Zhang, J. Xue, and N. Zheng · 2019
Cited alongside, same era.
Relational graph learning for crowd navigation
C. Chen, S. Hu, P. Nikdel, G. Mori, and M. Savva · 2020
Cited alongside, same era.
From crowd simulation to robot navigation in crowds
T. Fraichard and V. Levesy · 2020
Cited alongside, same era.
Multimodal trajectory prediction via topological invariance for navigation at uncontrolled intersections
J. Roh, C. Mavrogiannis, R. Madan, D. Fox, and S. Srinivasa S · 2020
Cited alongside, same era.
Human motion trajectory prediction: a survey
A. Rudenko, L. Palmieri, M. Herman, K. M. Kitani, D. M. Gavrila, and K. O. Arras · 2020
Cited alongside, same era.
Trajectron++: Dynamically-feasible trajectory forecasting with heterogeneous data
T. Salzmann, B. Ivanovic, P. Chakravarty, and M. Pavone · 2020
Cited alongside, same era.
An approach to deploy interactive robotic simulators on the web for HRI experiments: Results in social robot navigation
N. Tsoi, M. Hussein, O. Fugikawa, J. D. Zhao, and M. Vázquez · 2021
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Influencing behavioral attributions to robot motion during task execution
N. Walker, C. Mavrogiannis, S. S. Srinivasa, and M. Cakmak · 2021
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Group-based motion prediction for navigation in crowded environments
A. Wang, C. Mavrogiannis, and A. Steinfeld · 2021
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SocNavBench: A grounded simulation testing framework for evaluating social navigation
A. Biswas, A. Wang, G. Silvera, A. Steinfeld, and H. Admoni · 2022
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Social momentum: Design and evaluation of a framework for socially competent robot navigation
C. Mavrogiannis, P. Alves-Oliveira, W. Thomason, and R. A. Knepper · 2022
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A Protocol for Validating Social Navigation Policies
S. Pirk, E. Lee, X. Xiao, L. Takayama, A. Francis, and A. Toshev · 2022
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Towards Rich, Portable, and Large-Scale Pedestrian Data Collection
A. Wang, A. Biswas, H. Admoni, and A. Steinfeld · 2022
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Winding through: Crowd navigation via topological invariance
C. Mavrogiannis, K. Balasubramanian, S. Poddar, A. Gandra, and S. S. Srinivasa · 2023
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Core Challenges of Social Robot Navigation: A Survey
C. Mavrogiannis, F. Baldini, A. Wang, D. Zhao, P. Trautman, A. Steinfeld, and J. Oh · 2023
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