Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
125 tokens/sec
GPT-4o
47 tokens/sec
Gemini 2.5 Pro Pro
43 tokens/sec
o3 Pro
4 tokens/sec
GPT-4.1 Pro
47 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

Human Leading or Following Preferences: Effects on Human Perception of the Robot and the Human-Robot Collaboration (2401.01466v2)

Published 2 Jan 2024 in cs.RO

Abstract: Achieving effective and seamless human-robot collaboration requires two key outcomes: enhanced team performance and fostering a positive human perception of both the robot and the collaboration. This paper investigates the capability of the proposed task planning framework to realize these objectives by integrating human leading/following preferences and performance into its task allocation and scheduling processes. We designed a collaborative scenario wherein the robot autonomously collaborates with participants. The outcomes of the user study indicate that the proactive task planning framework successfully attains the aforementioned goals. We also explore the impact of participants' leadership and followership styles on their collaboration. The results reveal intriguing relationships between these factors which warrant further investigation in future studies.

Definition Search Book Streamline Icon: https://streamlinehq.com
References (39)
  1. doi:https://doi.org/10.1016/j.robot.2019.03.003.
  2. doi:10.3389/frobt.2021.725780.
  3. doi:10.1145/3568162.3576965.
  4. doi:10.1109/TASE.2018.2840345.
  5. doi:10.1109/IROS.2018.8593716.
  6. doi:10.1109/TASE.2021.3074873.
  7. doi:10.1109/RO-MAN53752.2022.9900872.
  8. doi:10.1109/THMS.2022.3230667.
  9. doi:10.3390/s22134901.
  10. doi:10.1109/LRA.2021.3056370.
  11. doi:10.1109/LRA.2019.2926963.
  12. doi:10.1109/ROMAN.2018.8525644.
  13. doi:10.1145/3472307.3484671.
  14. doi:10.1109/RO-MAN53752.2022.9900770.
  15. doi:10.1109/RO-MAN57019.2023.10309328.
  16. doi:10.1177/0278364919866905.
  17. doi:10.1145/3171221.3171264.
  18. doi:10.1080/00140139608964474.
  19. doi:10.3389/fpsyg.2019.00519.
  20. doi:10.1145/3594715.
  21. doi:10.1145/3025453.3025739.
  22. doi:10.1073/pnas.1807184115.
  23. doi:10.2139/ssrn.3816533.
  24. System-directed picking empower associates to empower associates to be more productive. URL https://6river.com/directed-picking/
  25. How robotic picking is revolutionizing warehouse productivity. URL https://www.dhl.com/global-en/delivered/digitalization/locus-robotics-robotic-picking.html
  26. doi:10.1145/3290605.3300750.
  27. doi:10.1109/IEEM45057.2020.9309971.
  28. doi:https://doi.org/10.1016/j.procir.2016.02.080.
  29. doi:10.1109/LRA.2022.3188906.
  30. doi:10.1145/3585276.
  31. doi:10.1109/ICRA48506.2021.9561649.
  32. doi:10.1177/0278364916688255.
  33. doi:10.1109/IROS40897.2019.8968543.
  34. doi:10.1145/3171221.3171267.
  35. doi:10.1109/IROS51168.2021.9636515.
  36. doi:10.1177/0278364917690593.
  37. doi:https://doi.org/10.1016/j.rcim.2018.11.011.
  38. doi:10.9781/ijimai.2017.09.001.
  39. doi:10.1109/THMS.2019.2904558.
Citations (1)

Summary

We haven't generated a summary for this paper yet.