SocNavBench
A Grounded Simulation Testing Framework for Evaluating Social Navigation
Bibliographic Data
| ID | 22190811 |
|---|---|
| Authors | Abhijat Biswas (0000-0003-4329-9738, Carnegie Mellon University), Allan Wang (0000-0002-6622-1610, Carnegie Mellon University), Gustavo Silvera (Carnegie Mellon University), Aaron Steinfeld (0000-0003-2274-0053, Carnegie Mellon University), Henny Admoni (0000-0003-1796-2196, Carnegie Mellon University) |
| Year | 2022 |
| Volume | 11 |
| Issue | 3 |
| Pages | 1-24 |
| Publication date | 2022-09-30 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | ACM Transactions on Human-Robot Interaction (JOURNAL) |
| Journal identifiers | ISSN: 2573-9522 • E-ISSN: 2573-9522 |
| Publisher | Association for Computing Machinery (ACM) (PUBLISHER) |
| DOI | 10.1145/3476413 |
| OpenAlex | W3134000433 |
| Language | EN |
| Citations received | 2 |
| References cited | 50 |
The human-robot interaction community has developed many methods for robots to navigate safely and socially alongside humans. However, experimental procedures to evaluate these works are usually constructed on a per-method basis. Such disparate evaluations make it difficult to compare the performance of such methods across the literature. To bridge this gap, we introduce SocNavBench , a simulation framework for evaluating social navigation algorithms. SocNavBench comprises a simulator with photo-realistic capabilities and curated social navigation scenarios grounded in real-world pedestrian data. We also provide an implementation of a suite of metrics to quantify the performance of navigation algorithms on these scenarios. Altogether, SocNavBench provides a test framework for evaluating disparate social navigation methods in a consistent and interpretable manner. To illustrate its use, we demonstrate testing three existing social navigation methods and a baseline method on SocNavBench , showing how the suite of metrics helps infer their performance trade-offs. Our code is open-source, allowing the addition of new scenarios and metrics by the community to help evolve SocNavBench to reflect advancements in our understanding of social navigation
Data mining · Data science · Human–computer interaction · Machine learning · Pedestrian · Programming language · Suite · Test case · Test suite · Transport engineering · Computer Science · Engineering · Evacuation and Crowd Dynamics · Social Robot Interaction and HRI · Video Surveillance and Tracking Methods · Artificial Intelligence
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Dynamic Social Zone based Mobile Robot Navigation for Human Comfortable Safety in Social Environments
| Unique citing works | 2 |
|---|---|
| Citations per year | 1 |
| Citation span | 2024 - 2025 (2) |
| Citation velocity | recent |
| Highly cited | No |
| Citation types | Neutral: 2 |