# Decentralized Structural-RNN for Robot Crowd Navigation with Deep Reinforcement Learning

arXiv: https://arxiv.org/abs/2011.04820 · HTML: https://mlsanity.com/paper/2011.04820/

## Key facts

- Cited by 40 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 9 Nov 2020.

## Built on by (most cited first, 30 of 40)

- [Intention Aware Robot Crowd Navigation with Attention-Based Interaction Graph](https://mlsanity.com/paper/2203.01821/) (2022)
- [Learning Sparse Interaction Graphs of Partially Detected Pedestrians for Trajectory Prediction](https://mlsanity.com/paper/2107.07056/) (2021)
- [From Cognition to Precognition: A Future-Aware Framework for Social Navigation](https://mlsanity.com/paper/2409.13244/) (2024)
- [Occlusion-Aware Crowd Navigation Using People as Sensors](https://mlsanity.com/paper/2210.00552/) (2022)
- [HabiCrowd: A High Performance Simulator for Crowd-Aware Visual Navigation](https://mlsanity.com/paper/2306.11377/) (2023)
- [DR-MPC: Deep Residual Model Predictive Control for Real-world Social Navigation](https://mlsanity.com/paper/2410.10646/) (2024)
- [HEIGHT: Heterogeneous Interaction Graph Transformer for Robot Navigation in Crowded and Constrained Environments](https://mlsanity.com/paper/2411.12150/) (2024)
- [Learning to Navigate Intersections with Unsupervised Driver Trait Inference](https://mlsanity.com/paper/2109.06783/) (2021)
- [SELFI: Autonomous Self-Improvement with Reinforcement Learning for Social Navigation](https://mlsanity.com/paper/2403.00991/) (2024)
- [Grounded Relational Inference: Domain Knowledge Driven Explainable Autonomous Driving](https://mlsanity.com/paper/2102.11905/) (2021)
- [Uncertainty-Aware DRL for Autonomous Vehicle Crowd Navigation in Shared Space](https://mlsanity.com/paper/2405.13969/) (2024)
- [Towards Generalizable Safety in Crowd Navigation via Conformal Uncertainty Handling](https://mlsanity.com/paper/2508.05634/) (2025)
- [From Obstacles to Etiquette: Robot Social Navigation with VLM-Informed Path Selection](https://mlsanity.com/paper/2602.09002/) (2026)
- [Meta-path Analysis on Spatio-Temporal Graphs for Pedestrian Trajectory Prediction](https://mlsanity.com/paper/2202.13427/) (2022)
- [Attention Graph for Multi-Robot Social Navigation with Deep Reinforcement Learning](https://mlsanity.com/paper/2401.17914/) (2024)
- [ComposableNav: Instruction-Following Navigation in Dynamic Environments via Composable Diffusion](https://mlsanity.com/paper/2509.17941/) (2025)
- [SocNavGym: A Reinforcement Learning Gym for Social Navigation](https://mlsanity.com/paper/2304.14102/) (2023)
- [Transformable Gaussian Reward Function for Socially-Aware Navigation with Deep Reinforcement Learning](https://mlsanity.com/paper/2402.14569/) (2024)
- [HeR-DRL:Heterogeneous Relational Deep Reinforcement Learning for Decentralized Multi-Robot Crowd Navigation](https://mlsanity.com/paper/2403.10083/) (2024)
- [Exploring Social Motion Latent Space and Human Awareness for Effective Robot Navigation in Crowded Environments](https://mlsanity.com/paper/2310.07335/) (2023)
- [Online Context Learning for Socially Compliant Navigation](https://mlsanity.com/paper/2406.11495/) (2024)
- [Socially aware navigation for mobile robots: a survey on deep reinforcement learning approaches](https://mlsanity.com/paper/2512.00049/) (2025)
- [EvoNav: Evolutionary Reward Function Design for Robot Navigation with Large Language Models](https://mlsanity.com/paper/2605.11859/) (2026)
- [MeSA-DRL: Memory-Enhanced Deep Reinforcement Learning for Advanced Socially Aware Robot Navigation in Crowded Environments](https://mlsanity.com/paper/2404.05203/) (2024)
- [CoNav: A Benchmark for Human-Centered Collaborative Navigation](https://mlsanity.com/paper/2406.02425/) (2024)
- [Don't Freeze, Don't Crash: Extending the Safe Operating Range of Neural Navigation in Dense Crowds](https://mlsanity.com/paper/2603.06729/) (2026)
- [Relative velocity-based reward functions for crowd navigation of robots](https://mlsanity.com/paper/2112.13984/) (2021)
- [Multi-robot Social-aware Cooperative Planning in Pedestrian Environments Using Multi-agent Reinforcement Learning](https://mlsanity.com/paper/2211.15901/) (2022)
- [Conveying Autonomous Robot Capabilities through Contrasting Behaviour Summaries](https://mlsanity.com/paper/2304.00367/) (2023)
- [Learned Tree Search for Long-Horizon Social Robot Navigation in Shared Airspace](https://mlsanity.com/paper/2304.01428/) (2023)

## Abstract (arXiv)

Safe and efficient navigation through human crowds is an essential capability for mobile robots. Previous work on robot crowd navigation assumes that the dynamics of all agents are known and well-defined. In addition, the performance of previous methods deteriorates in partially observable environments and environments with dense crowds. To tackle these problems, we propose decentralized structural-Recurrent Neural Network (DS-RNN), a novel network that reasons about spatial and temporal relationships for robot decision making in crowd navigation. We train our network with model-free deep reinforcement learning without any expert supervision. We demonstrate that our model outperforms previous methods in challenging crowd navigation scenarios. We successfully transfer the policy learned in the simulator to a real-world TurtleBot 2i. For more information, please visit the project website at https://sites.google.com/view/crowdnav-ds-rnn/home.