Souravik Dutta | NTU Singapore | Intelligent Robotics

Preprint

Ridhima Bector, Souravik Dutta, Poornima Ramachandran, Ree Yan Yeoh, Jui Hien Tan, Domenico Campolo, Bernhard Johannes Schmitt
2026

DOI: 10.48550/arXiv.2607.13696

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APA Click to copy
Bector, R., Dutta, S., Ramachandran, P., Yeoh, R. Y., Tan, J. H., Campolo, D., & Schmitt, B. J. (2026). Anatomy of Uncertainty: Expressive Descriptors of Robot Motion for Nonverbal Human-Robot Communication. https://doi.org/10.48550/arXiv.2607.13696

Chicago/Turabian Click to copy
Bector, Ridhima, Souravik Dutta, Poornima Ramachandran, Ree Yan Yeoh, Jui Hien Tan, Domenico Campolo, and Bernhard Johannes Schmitt. “Anatomy of Uncertainty: Expressive Descriptors of Robot Motion for Nonverbal Human-Robot Communication,” 2026.

MLA Click to copy
Bector, Ridhima, et al. Anatomy of Uncertainty: Expressive Descriptors of Robot Motion for Nonverbal Human-Robot Communication. 2026, doi:10.48550/arXiv.2607.13696.

BibTeX Click to copy

@unpublished{ridhima2026a,
  title = {Anatomy of Uncertainty: Expressive Descriptors of Robot Motion for Nonverbal Human-Robot Communication},
  year = {2026},
  doi = {10.48550/arXiv.2607.13696},
  author = {Bector, Ridhima and Dutta, Souravik and Ramachandran, Poornima and Yeoh, Ree Yan and Tan, Jui Hien and Campolo, Domenico and Schmitt, Bernhard Johannes}
}

Abstract

Robots working alongside humans must communicate their intended actions together with the uncertainty that arises from incomplete or ambiguous perception. This paper introduces a mathematical framework for expressing perceptual uncertainty through the motion of a robotic manipulator. Drawing on concepts of approach-avoidance and active perception, robot behavior is organized in a Commitment-Vigilance state space whose dimensions are represented through Laban Effort factors, mapping five uncertainty-related states, namely confidence, curiosity, hesitance, fear and inactivity on the uncertainty continuum. A kinematic analysis decomposes goal-directed end-effector motion into a radial task-progress rate and a tangential target-bearing rate, which realize the two dimensions. From this decomposition, five motion primitives, namely approach, pause, retreat, probe and twitch, are derived and parameterized using eleven kinematic descriptors covering approach and retreat characteristics, pause behavior, gaze angles, end-effector tilt and shiver amplitude. A video-based human-subject study evaluated the recognition of uncertainty-expressive trajectories and the influence of individual descriptors on perceived intensity. For every trajectory the intended behavioral state was the modal response and was selected significantly more often than chance. In single-descriptor comparisons, participants significantly preferred one variant as the more intense expression of the intended state. The results provide a perceptual basis for encoding robot uncertainty in motion and for generating such trajectories autonomously from parametric movement representations.

Keywords

Expressive motion
Robotic manipulator
Perceptual uncertainty
Nonverbal communication
Laban Movement Analysis
Human-robot collaboration