RESONATE: a Real Social Navigation Testbed for Autonomous Service Robots
RESONATE: a Real Social Navigation Testbed for Autonomous Service Robots
This research presents RESONATE, a reproducible benchmark for human-aware navigation of autonomous service robots. The testbed utilizes a unified robotic platform and ROS 2 software stack to evaluate eight controller configurations across eight scenarios with five repetitions each, totaling 320 physical experiments. Results identify DWA with Gaussian social costmaps as reliable and SFM-MPPI as offering the best balance between robustness, efficiency, and social acceptance, providing reusable baselines and data for advancing socially aware navigation research.
The paper introduces RESONATE, a reproducible benchmark for autonomous service robots that combines quantitative metrics with qualitative social assessments across 320 physical experiments to evaluate eight controller configurations.
Source: arXiv Robotics — research abstracts · Read original article ↗
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What the source reports
Publisher-reported claims, with original evidence. These results have not been independently verified by RoboSignal.
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- Reported autonomousOpen source S2
Reported numbers
physical experiments
320
Reported trials
View original evidence
ajectory ground truth, and structured social interaction scenarios. We evaluate eight controller configurations, combining classical and predictive local planners with different social modeling strategies, over eight representative scenarios with five repetitions each, yielding 320 physical experiments. The benchmark combines quantitative navigation and social metrics with participant-based qualitative assessments to
Open source S3scenarios
8
View original evidence
ajectory ground truth, and structured social interaction scenarios. We evaluate eight controller configurations, combining classical and predictive local planners with different social modeling strategies, over eight representative scenarios with five repetitions each, yielding 320 physical experiments. The benchmark combines quantitative navigation and social metrics with participant-based qualitative assessments to
Open source S3repetitions per scenario
5
View original evidence
ajectory ground truth, and structured social interaction scenarios. We evaluate eight controller configurations, combining classical and predictive local planners with different social modeling strategies, over eight representative scenarios with five repetitions each, yielding 320 physical experiments. The benchmark combines quantitative navigation and social metrics with participant-based qualitative assessments to
Open source S3controller configurations
8
View original evidence
ajectory ground truth, and structured social interaction scenarios. We evaluate eight controller configurations, combining classical and predictive local planners with different social modeling strategies, over eight representative scenarios with five repetitions each, yielding 320 physical experiments. The benchmark combines quantitative navigation and social metrics with participant-based qualitative assessments to
Open source S3
- paper: not_reported
- code: not_reported
- weights: not_reported
- dataset: not_reported
What remains unknown
Dataset licensing and commercial-use rights are not established here.
Source excerpts and review record
Automatically extracted; no manual editorial approval recorded.
ajectory ground truth, and structured social interaction scenarios. We evaluate eight controller configurations, combining classical and predictive local planners with different social modeling strategies, over eight representative scenarios with five repetitions each, yielding 320 physical experiments. The benchmark combines quantitative navigation and social metrics with participant-based qualitative assessments to
Open source S3
arXiv:2611.02937v1 Announce Type: new Abstract: Social navigation is essential for autonomous service robots operating in human environments, but progress remains constrained by the lack of extensive real-world benchmarks. This paper presents the Real Social Navigation Testbed (RESONATE), a reproducible benchmark for human-aware navigation based on a unified robotic platform, a shared ROS 2 software stack, precise tr
Open source S2
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Source：arXiv Robotics — research abstracts · arxiv.org