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1724591 Vol 10 · Issue 5 Download Paper

Model-Based Evaluation of Dynamic Safety Control for Human–Robot Collaboration

Jaivant N Ritesh G Anbarasi M. P.

Subject area: Science,Engineering and Technology  ·  Area of research: Robotics and Automation

Abstract

In this paper we explore how a safety controller on a robot reacts to a person passing near it when sensor data arrives to it in a delayed manner. The work is concentrated on a 2D-model involving a fixed-speed controller and dynamic controller in three situations, namely a person passing the path of the vehicle, passing diagonally toward the vehicle, and a slowly passing person, and comparing results. Each run keeps track of the minimum separation distance between the robot and person and occurrences wherein they collide, and also distance and time spent around the safety threshold (around minimum distance), besides average speed of robot. For each test, the minimum separation distance, number of collision points, time inside range and average robot speed are recorded. Both the crossing and slow-approach have no collisions under the dynamic controller. The static collision for the crossing test at -0.281 is replaced with a comfortable safety margin of 1.263m. The Diagonal still collides with minimum clearance of -0.628m. Slowing down a robot with delayed distance readings becomes safer in the simplest cases, failing when person future movement goes unnoted by the controller.

Keywords

human robot collaboration; robot safety; sensor latency; collision avoidance; braking distance; dynamic speed controller

References

[1] Marvel JA, Norcross R. Implementing speed and separation monitoring in collaborative robot workcells. Robotics and Computer-Integrated Manufacturing. 2017;44:144–155. https://doi.org/10.1016/j.rcim.2016.08.001

[2] Lucci N, Zanchettin AM, Rocco P. Combining speed and separation monitoring with power and force limiting for safe collaborative robotics applications. IEEE Robotics and Automation Letters. 2020;5(4):6631–6638. https://doi.org/10.1109/LRA.2020.3011852

[3] Villani V, Pini F, Leali F, Secchi C. Survey on human–robot collaboration in industrial settings. Mechanism and Machine Theory. 2019;131:248–266. https://doi.org/10.1016/j.mechmachtheory.2018.10.009

[4] Li W, et al. Safe human–robot collaboration for industrial settings: A survey. Journal of Intelligent Manufacturing. 2024. https://doi.org/10.1007/s10845-023-02159-4

[5] Liu H, et al. Collision-free human–robot collaboration based on context awareness. Robotics and Computer-Integrated Manufacturing. 2021.

How to cite this paper

Jaivant N, Ritesh G, Anbarasi M. P. "Model-Based Evaluation of Dynamic Safety Control for Human–Robot Collaboration" Iconic Research And Engineering Journals Volume 10 Issue 5 2026 Page 469-476
Jaivant N, Ritesh G, Anbarasi M. P. "Model-Based Evaluation of Dynamic Safety Control for Human–Robot Collaboration" Iconic Research And Engineering Journals, vol. 10, no. 5, Nov. 2026
Jaivant N, Ritesh G, Anbarasi M. P. (2026). Model-Based Evaluation of Dynamic Safety Control for Human–Robot Collaboration. Iconic Research And Engineering Journals, 10(5).
Jaivant N, Ritesh G, Anbarasi M. P. "Model-Based Evaluation of Dynamic Safety Control for Human–Robot Collaboration" Iconic Research And Engineering Journals, vol. 10, no. 5, Nov. 2026.
@article{1724591,
      author = {Jaivant N, Ritesh G, Anbarasi M. P.},
      title = {Model-Based Evaluation of Dynamic Safety Control for Human–Robot Collaboration},
      journal = {Iconic Research And Engineering Journals},
      year = {2026},
      volume = {10},
      number = {5},
      pages = {469-476},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1724591.pdf},
      abstract = {In this paper we explore how a safety controller on a robot reacts to a person passing near it when sensor data arrives to it in a delayed manner. The work is concentrated on a 2D-model involving a fixed-speed controller and dynamic controller in three situations, namely a person passing the path of the vehicle, passing diagonally toward the vehicle, and a slowly passing person, and comparing results. Each run keeps track of the minimum separation distance between the robot and person and occurrences wherein they collide, and also distance and time spent around the safety threshold (around minimum distance), besides average speed of robot. For each test, the minimum separation distance, number of collision points, time inside range and average robot speed are recorded. Both the crossing and slow-approach have no collisions under the dynamic controller. The static collision for the crossing test at -0.281 is replaced with a comfortable safety margin of 1.263m. The Diagonal still collides with minimum clearance of -0.628m. Slowing down a robot with delayed distance readings becomes safer in the simplest cases, failing when person future movement goes unnoted by the controller.},
      keywords = {human robot collaboration; robot safety; sensor latency; collision avoidance; braking distance; dynamic speed controller},
      month = {November},
  }