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Social Zone as a Barrier Function for Socially-Compliant Robot Navigation (2405.15101v2)

Published 23 May 2024 in cs.RO, cs.SY, and eess.SY

Abstract: This study addresses the challenge of integrating social norms into robot navigation, which is essential for ensuring that robots operate safely and efficiently in human-centric environments. Social norms, often unspoken and implicitly understood among people, are difficult to explicitly define and implement in robotic systems. To overcome this, we derive these norms from real human trajectory data, utilizing the comprehensive ATC dataset to identify the minimum social zones humans and robots must respect. These zones are integrated into the robot's navigation system by applying barrier functions, ensuring the robot consistently remains within the designated safety set. Simulation results demonstrate that our system effectively mimics human-like navigation strategies, such as passing on the right side and adjusting speed or pausing in constrained spaces. The proposed framework is versatile, easily comprehensible, and tunable, demonstrating the potential to advance the development of robots designed to navigate effectively in human-centric environments.

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References (33)
  1. Control barrier functions: Theory and applications. In 2019 18th European control conference (ECC), 3420–3431. IEEE.
  2. Lof: identifying density-based local outliers. In Proceedings of the 2000 ACM SIGMOD international conference on Management of data, 93–104.
  3. Person tracking in large public spaces using 3-d range sensors. IEEE Transactions on Human-Machine Systems, 43(6), 522–534.
  4. Physics-based modeling and data representation of pairwise interactions among pedestrians. Physical review E, 98(6), 062310.
  5. Principles and guidelines for evaluating social robot navigation algorithms. arXiv preprint arXiv:2306.16740.
  6. Human-robot matching and routing for multi-robot tour guiding under time uncertainty. arXiv preprint arXiv:2309.15373.
  7. Smallest enclosing ellipses: fast and exact.
  8. Characteristics of personal space during obstacle circumvention in physical and virtual environments. Gait & posture, 27(2), 239–247.
  9. Hall, E.T. (1963). A system for the notation of proxemic behavior. American anthropologist, 65(5), 1003–1026.
  10. Hayduk, L.A. (1981). The shape of personal space: An experimental investigation. Canadian Journal of Behavioural Science/Revue canadienne des sciences du comportement, 13(1), 87.
  11. Providers-clients-robots: Framework for spatial-semantic planning for shared understanding in human-robot interaction. In 2022 31st IEEE International Conference on Robot and Human Interactive Communication (RO-MAN), 1099–1106. IEEE.
  12. Companion: A constraint-optimizing method for person-acceptable navigation. In RO-MAN 2009-The 18th IEEE International Symposium on Robot and Human Interactive Communication, 607–612. IEEE.
  13. Pedestrian vision and collision avoidance behavior: Investigation of the information process space of pedestrians using an eye tracker. In Pedestrian and evacuation dynamics 2008, 95–108. Springer.
  14. Review of pedestrian trajectory prediction methods: Comparing deep learning and knowledge-based approaches. IEEE Transactions on Intelligent Transportation Systems, 23(12), 24126–24144.
  15. Socially compliant mobile robot navigation via inverse reinforcement learning. The International Journal of Robotics Research, 35(11), 1289–1307.
  16. Crowds by example. In Computer graphics forum, volume 26, 655–664. Wiley Online Library.
  17. Core challenges of social robot navigation: A survey. ACM Transactions on Human-Robot Interaction, 12(3), 1–39.
  18. A survey on human-aware robot navigation. Robotics and Autonomous Systems, 145, 103837.
  19. Determining shape and size of personal space of a human when passed by a robot. International Journal of Social Robotics, 14(2), 561–572.
  20. The effect of robot speed on comfortable passing distances. Frontiers in Robotics and AI, 9, 915972.
  21. Learning proxemics for personalized human–robot social interaction. International Journal of Social Robotics, 12, 267–280.
  22. You’ll never walk alone: Modeling social behavior for multi-target tracking. In 2009 IEEE 12th international conference on computer vision, 261–268. IEEE.
  23. High-statistics pedestrian dynamics on stairways and their probabilistic fundamental diagrams. Transportation research part C: emerging technologies, 159, 104468.
  24. From proxemics theory to socially-aware navigation: A survey. International Journal of Social Robotics, 7, 137–153.
  25. Learning social etiquette: Human trajectory understanding in crowded scenes. In European conference on computer vision, 549–565. Springer.
  26. Implicit functions with guaranteed differential properties. In Proceedings of the fifth ACM symposium on Solid modeling and applications, 258–269.
  27. Trajectory planning for robots in dynamic human environments. In 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems, 4293–4298. IEEE.
  28. Toward safety-aware informative motion planning for legged robots. arXiv preprint arXiv:2103.14252.
  29. Dynamic social zone based mobile robot navigation for human comfortable safety in social environments. International Journal of Social Robotics, 8, 663–684.
  30. On the implementation of an interior-point filter line-search algorithm for large-scale nonlinear programming. Mathematical programming, 106, 25–57.
  31. Social distances model of pedestrian dynamics. In Cellular Automata: 7th International Conference on Cellular Automata, for Research and Industry, ACRI 2006, Perpignan, France, September 20-23, 2006. Proceedings 7, 492–501. Springer.
  32. Understanding pedestrian behaviors from stationary crowd groups. In Proceedings of the IEEE conference on computer vision and pattern recognition, 3488–3496.
  33. Safety-critical model predictive control with discrete-time control barrier function. In 2021 American Control Conference (ACC), 3882–3889. IEEE.
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Authors (2)
  1. Junwoo Jang (3 papers)
  2. Maani Ghaffari (70 papers)