The DOI matches its Crossref record; 49 of the 49 references it cites were found in a registry or an index.
Crowd-Robot Interaction: Crowd-Aware Robot Navigation With Attention-Based Deep Reinforcement Learning
Open accessAbstract
Mobility in an effective and socially-compliant manner is an essential yet challenging task for robots operating in crowded spaces. Recent works have shown the power of deep reinforcement learning techniques to learn socially cooperative policies. However, their cooperation ability deteriorates as the crowd grows since they typically relax the problem as a one-way Human-Robot interaction problem. In this work, we want to go beyond first-order Human-Robot interaction and more explicitly model Crowd-Robot Interaction (CRI). We propose to (i) rethink pairwise interactions with a self-attention mechanism, and (ii) jointly model Human-Robot as well as Human-Human interactions in the deep reinforcement learning framework. Our model captures the Human-Human interactions occurring in dense crowds that indirectly affects the robot's anticipation capability. Our proposed attentive pooling mechanism learns the collective importance of neighboring humans with respect to their future states. Various experiments demonstrate that our model can anticipate human dynamics and navigate in crowds with time efficiency, outperforming state-of-the-art methods.
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Human-level control through deep reinforcement learning
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Cited by
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de Santana Correia, A., & Colombini, E. L. (2022) · Artificial Intelligence Review · doi:10.1007/s10462-022-10148-x · Cited by 298
Human Trajectory Forecasting in Crowds: A Deep Learning Perspective
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Self-citationPrinciples and Guidelines for Evaluating Social Robot Navigation Algorithms
Francis, A., Pérez-D’Arpino, C., Li, C., Xia, F., Alahi, A., Alami, R., Bera, A., Biswas, A., Biswas, J., Chandra, R., et al. (2025) · ACM Transactions on Human-Robot Interaction · doi:10.1145/3700599 · Cited by 107
Self-citationDirected Acyclic Graph Neural Network for Human Motion Prediction
Li, Q., Chalvatzaki, G., Peters, J., & Wang, Y. (2021) · 2021 IEEE International Conference on Robotics and Automation (ICRA) · doi:10.1109/icra48506.2021.9561540 · Cited by 29
Balaji, B., Mallya, S., Genc, S., Gupta, S., Dirac, L., Khare, V., Roy, G., Sun, T., Tao, Y., Townsend, B., et al. (2019) · arXiv · doi:10.48550/arxiv.1911.01562 · Cited by 27
Metadata
- Authors
- Chen, C., Liu, Y., Kreiss, S., & Alahi, A.
- Venue
- 2019 International Conference on Robotics and Automation (ICRA)
- Publisher
- IEEE
- Published
- 2019-05
- Pages
- 6015-6022
- ISSN
- 1050-4729 (ISSN-L)
- OpenAlex
- W2890001928
- Cited by
- 615
- References
- 49
- FWCI
- 23.44
- Type
- conference paper
- Language
- en
- Open access
- green
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- Chen, C., Liu, Y., Kreiss, S., & Alahi, A. (2019). Crowd-Robot Interaction: Crowd-Aware Robot Navigation With Attention-Based Deep Reinforcement Learning. 2019 International Conference on Robotics and Automation (ICRA). https://doi.org/10.1109/icra.2019.8794134
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