A short methodological review on social robot navigation benchmarking
Social Robot Navigation is the skill that allows robots to move efficiently in human-populated environments while ensuring safety, comfort, and trust. Unlike other areas of research, the scientific community has not yet achieved an agreement on how Social Robot Navigation should be benchmarked. This is notably important, as the lack of a de facto standard to benchmark Social Robot Navigation can hinder the progress of the field and may lead to contradicting conclusions. Motivated by this gap, we contribute with a short review focused exclusively on benchmarking trends in the period from January 2020 to July 2025. Of the 130 papers identified by our search using IEEE Xplore, we analysed the 85 papers that met the criteria of the review. This review addresses the metrics used in the literature for benchmarking purposes, the algorithms employed in such benchmarks, the use of human surveys for benchmarking, and how conclusions are drawn from the benchmarking results, when applicable.
Code (0)
등록된 구현이 없습니다.
Tasks
Robot NavigationSimilar Papers 제목 키워드 기반
Optimal-Horizon Social Robot Navigation in Heterogeneous Crowds
Navigating social robots in dense, dynamic crowds is challenging due to environmental uncertainty and complex human-robot interactions. While Model Predictive Control (MPC) offers strong real-time performance, its relian…
Reinforcement LearningRobot NavigationExploring Social Motion Latent Space and Human Awareness for Effective Robot Navigation in Crowded Environments
This work proposes a novel approach to social robot navigation by learning to generate robot controls from a social motion latent space. By leveraging this social motion latent space, the proposed method achieves signifi…
Robot NavigationSocial NavigationGROVE: Grounded Pedestrian Simulation via Natural Language for Interactive Social Robot Navigation
Pedestrian simulation is a critical component for training and deploying social robot navigation approaches, yet it remains a largely rigid system that repeatedly requires manual data generation to define even simple sce…
Robot NavigationSocialNav-SUB: Benchmarking VLMs for Scene Understanding in Social Robot Navigation
Robot navigation in dynamic, human-centered environments requires socially-compliant decisions grounded in robust scene understanding. Recent Vision-Language Models (VLMs) exhibit promising capabilities such as object re…
Visual Question AnsweringScene UnderstandingObject RecognitionRobot NavigationPrinciples and Guidelines for Evaluating Social Robot Navigation Algorithms
A major challenge to deploying robots widely is navigation in human-populated environments, commonly referred to as social robot navigation. While the field of social navigation has advanced tremendously in recent years,…
BenchmarkingRobot NavigationSocial Navigation