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An Affordance and Distance Minimization Based Method for Computing Object Orientations for Robot Human Handovers

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Abstract

The ability to hand over objects to humans is an important skill for service robots. However, determining the proper object pose for handover is a challenging task. Our approach, based on observations of a set of natural human handovers, addresses three related challenges in teaching robots how to hand over objects: (1) how to compute mathematically an appropriate ‘standard’ or ‘mean’ handover orientation, (2) how to ascertain whether an observed set is of good or poor quality, and (3) using (1) and (2), how to compute an appropriate handover orientation from a set, in a manner that is robust to the quality of the set. We first compare three methods for computing mean orientations and show that our proposed distance minimization based method yields the best results. Next, we show that using the concept of affordance axes, we can evaluate the quality of a set of observed orientations. Finally, using affordance axes together with random sample consensus, we devise a method for computing an appropriate handover orientation from a set of observed natural handover orientations. User study data verified that our methods are successful in identifying both good and poor quality sets of handover orientations and in computing appropriate handover orientations from observed natural handover orientations. These results enable robots to automatically learn proper handover orientations for various objects.

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References

  1. Chan WP, Kumagai I, Nozawa S, Kakiuchi Y, Okada K, Inaba M (2013) Creating socially acceptable robots: leaning grasp configurations for object handovers from demonstrations. In: Workshop on advanced robotics and its social impacts, pp 94–99

  2. Xu Y et al (2003) Development of a hospital service robot for transporting task. In: International conference on robotics, intelligent systems and signal processing, pp 628–633

  3. Diftler M, Mehling J, Abdallah M (2011) Robonaut 2—the first humanoid robot in space. In: International conference on robotics and automation, pp 2178–2183

  4. Akella P, Peshkin M (1999) Cobots for the automobile assembly line. In: International conference on robotics & automation, pp 728–733

  5. Wallhoff F, Blume J, Bannat A, Rösel W, Lenz C, Knoll A (2010) A skill-based approach towards hybrid assembly. Adv Eng Inform 24(3):329–339

    Article  Google Scholar 

  6. Wilcox R, Nikolaidis S, Shah J (2012) Optimization of temporal dynamics for adaptive human–robot interaction in assembly manufacturing. In: Robotics: science and systems

  7. Unhelkar VV, Siu HC, Shah JA (2014) Comparative performance of human and mobile robotic assistants in collaborative fetch-and-deliver tasks. In: Proceedings ACM/IEEE International Conference on Human-Robot Interaction, pp 82–89

  8. Iwamura Y, Shiomi M, Kanda T, Ishiguro H, Hagita N (2011) Do elderly people prefer a conversational humanoid as a shopping assistant partner in supermarkets?. In: International conference on human–robot interaction, pp 449–456

  9. Kao Y-H, Wang W-J (2012) Design and implementation of a family robot. In: International joint conference on computer science and software engineering, pp 218–225

  10. Shibata T, Kawaguchi Y, Wada K (2009) Investigation on people living with Paro at home effects of sex difference and owners’ animal preference. In: International workshop on robot and human interactive communication, pp 1131–1136

  11. Wada K, Ikeda Y, Inoue K, Uehara R (2010) Development and preliminary evaluation of a caregiver’s manual for robot therapy using the therapeutic seal robot Paro. In: International workshop on robot and human interactive communication, pp 533–538

  12. Yamazaki K et al (2007) Prior-to-request and request behaviors within elderly day care : Implications for developing service robots for use in multiparty settings. In: European conference on computer supported cooperative work, pp 24–28

  13. Choi YS, Chen T, Jain A, Anderson C, Glass JD, Kemp CC (2009) Hand it over or set it down: a user study of object delivery with an assistive mobile manipulator. In: International symposium on robot and human interactive communication, pp 736–743

  14. Hart JW, Sheikholeslami S, Pan MKXJ, Chan WP, Croft EA (2015) Predictions of human task performance and handover trajectories for human–robot interaction. In: HRI 2015 workshop on human–robot teaming

  15. Strabala K et al (2013) Towards seamless human–robot handovers. J Hum Robot Interact 1(1):1–23

    Google Scholar 

  16. Cakmak M, Srinivasa SS, Lee MK, Kiesler S, Forlizzi J (2011) Using spatial and temporal contrast for fluent robot-human hand-overs. In: International conference on human robot interaction, pp 489–496

  17. Moon A, Troniak D, Gleeson B (2014) Meet me where I’m gazing: how shared attention gaze affects human–robot handover timing. In: International conference on human–robot interaction, pp 334–341

  18. Gharbi M, Paubel P-V, Clodic A, Carreras O, Alami R, Cellier J-M (2015) Toward a better understanding of the communication cues involved in a human–robot object transfer. In: Symposium on robot and human interactive communication, pp 319–324

  19. Shibata S, Tanaka K, Shimizu A (1995) Experimental analysis of handing over. In: Proceedings 4th IEEE international workshop on robot and human communication, pp 53–58

  20. Huber M, Rickert M, Knoll A, Brandt T, Glasauer S (2008) Human–robot interaction in handing-over tasks. In: International symposium on robot and human interactive communication, pp 107–112

  21. Mason AH, MacKenzie CL (2005) Grip forces when passing an object to a partner. Exp Brain Res 163(2):173–187

    Article  Google Scholar 

  22. Chan WP, Parker CAC, Van der Loos HFM, Croft EA (2013) A human-inspired object handover controller. Int J Robot Res 32(8):971–983

    Article  Google Scholar 

  23. Sisbot EA, Alami R (2012) A human-aware manipulation planner. IEEE Trans Robot 28(5):1045–1057

    Article  Google Scholar 

  24. Kim J, Park J, Hwang YK, Lee MJ (2004) Advanced grasp planning for handover operation between human and robot: three handover methods in esteem etiquettes using dual arms and hands of home-service robot. In: 2nd international conference on autonomous robots and agents, pp 34–39

  25. Cakmak M, Srinivasa SS, Lee MK, Forlizzi J, Kiesler S (2011) Human preferences for robot-human hand-over configurations. In: International conference on intelligent robots and systems, pp 1986–1993

  26. Aleotti J, Micelli V, Caselli S (2014) An affordance sensitive system for robot to human object handover. Int J Soc Robot 6(4):653–666

    Article  Google Scholar 

  27. Chan WP, Nagahama K, Yaguchi H, Kakiuchi Y, Okada K, Inaba M (2015) Implementation of a framework for learning handover grasp configurations through observation during human–robot object handovers. In: Humanoids, pp 1115–1120

  28. Gibson JJ (1979) “The Theory of Affordances”, in The ecological approach to visual perception: classic edition, Hillsdale. Lawrence Erlbaum Associates Inc., Mahwah

    Google Scholar 

  29. Norman D (2002) Design of everyday things: revised and expanded. Basic Books, New York

    Google Scholar 

  30. Curtis WD, Janin AL, Zikan K (1993) A note on averaging rotations. In: Virtual reality annual international symposium, no. 2, pp 377–385

  31. Gramkow C (2001) On averaging rotations. J Math Imaging Vis 15(1–2):7–16

    Article  MathSciNet  Google Scholar 

  32. Sharf I, Wolf A, Rubin MB (2010) Arithmetic and geometric solutions for average rigid-body rotation. Mech Mach Theory 45(9):1239–1251

    Article  Google Scholar 

  33. Hartley R, Trumpf J, Dai Y, Li H (2013) Rotation averaging. Int J Comput Vis 103(3):267–305

    Article  MathSciNet  Google Scholar 

  34. Chan WP, Pan MKXJ, Croft EA, Inaba M (2015) Characterization of handover orientations used by humans for efficient robot to human handovers. In: International conference on intelligent robots and systems, pp 1–6

  35. Huber M, Knoll A, Brandt T, Glasauer S (2009) Handing over a cube: spatial features of physical joint-action. Ann N Y Acad Sci 1164:380–382

    Article  Google Scholar 

  36. Hansen C, Arambel P, Ben Mansour K, Perdereau V, Marin F (2017) Human–human handover tasks and how distance and object mass matter. Percept Mot Skills 124(1):182–199

    Article  Google Scholar 

  37. Basili P, Huber M, Brandt T, Hirche S, Glasauer S (2009) Investigating human–human approach and hand-over. Hum Cent Robot Syst 6:151–160

    Article  Google Scholar 

  38. Koay KL, Sisbot EA, Syrdal DS, Walters ML, Dautenhahn K, Alami R (2007) Exploratory studies of a robot approaching a person in the context of handing over an object. In: AAAI spring symposium: multidisciplinary collaboration for socially assistive robotics, vol 33, pp 18–24

  39. Walters ML, Dautenhahn K, Woods SN, Koay KL (2007) Robotic etiquette: results from user studies involving a fetch and carry task. In: International conference on human–robot interaction, pp 317–324

  40. Mainprice J, Gharbi M, Simeon T, Alami R (2012) Sharing effort in planning human–robot handover tasks. In: Proceedings IEEE international workshop on robot and human interactive communication, pp 764–770

  41. Mainprice J, Sisbot EA, Siméon T, Alami R (2010) Planning Safe and Legible Hand-over Motions for Human-Robot Interaction. In: Proceedings IARP/IEEE-RAS/EURON workshop on technical challenges for dependable robots in human environments

  42. Dehais F, Sisbot EA, Alami R, Causse M (2011) Physiological and subjective evaluation of a human–robot object hand-over task. Appl Ergon 42(6):785–791

    Article  Google Scholar 

  43. Kulić D, Croft E (2007) Physiological and subjective responses to articulated robot motion. Robotica 25(1):13–27

    Article  Google Scholar 

  44. Chan WP, Parker CAC, Van der Loos HFM, Croft EA (2012) Grip forces and load forces in handovers: implications for designing human–robot handover controllers. In: International conference on human–robot interaction, pp 9–16

  45. Aleotti J, Micelli V, Caselli S (2012) Comfortable robot to human object hand-over. In: International workshop on robot and human interactive communication, pp 771–776

  46. Lu F, Milios E (1997) Globally consistent range scan alignment for environment mapping. Auton Robots 4(4):333–349

    Article  Google Scholar 

  47. Agrawal M (2006) A lie algebraic approach for consistent pose registration for general euclidean motion. In: IEEE international conference on intelligent robots and systems, pp 1891–1897

  48. Park FC, Martin BJ (1994) Robot sensor calibration: solving AX = XB on the Euclidean group. IEEE Trans Robot Autom 10(5):717–721

    Article  Google Scholar 

  49. Daniilidis K (1998) Hand-eye calibration using dual quaternions. Int J Robot Res 18:286–298

    Article  Google Scholar 

  50. Zhuang H (1998) Hand/eye calibration for electronic assembly robots. IEEE Trans Robot Autom 14(4):612–616

    Article  MathSciNet  Google Scholar 

  51. Strobl KH, Hirzinger G (2006) Optimal hand-eye calibration. In: IEEE international conference on intelligent robots and systems, no 3, pp 4647–4653

  52. Moakher M (2002) Means and averaging in the group of rotations. SIAM J Matrix Anal Appl 24(1):1–16

    Article  MathSciNet  Google Scholar 

  53. Markley FL, Cheng Y, Crassidis JL, Oshman Y (2007) Averaging quaternions. J Guid Control Dyn 30:1193–1196

    Article  Google Scholar 

  54. Shibata S, Sahbi BM, Tanaka K, Shimizu A (1997) An analysis of the process of handing over an object and its application to robot motions. In: International conference on systems, man, and cybernetics, pp 64–69

  55. Fischler MA, Bolles RC (1981) Random sample consensus: a paradigm for model fitting with. Commun. ACM 24:381–395

    Article  Google Scholar 

  56. Bicici E, Amant RS (2003) Reasoning about the functionality of tools and physical artifacts. Department of Computer Science, North Carolina State University

  57. Chan WP, Kakiuchi Y, Okada K, Inaba M (2014) Determining proper grasp configurations for handovers through observation of object movement patterns and inter-object interactions during usage. In: International conference on intelligent robots and systems, pp 1355–1360

  58. Aleotti J, Caselli S (2012) A 3D shape segmentation approach for robot grasping by parts. Robot Auton Syst 60(3):358–366

    Article  Google Scholar 

  59. Matsumaru T (2009) Handover movement informing receiver of weight load as informative motion study for human–friendly robot. In: International symposium on robot and human interactive communication, pp 299–305

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Author information

Authors and Affiliations

  1. Department of Mechanical Engineering, University of British Columbia, Vancouver, BC, Canada

    Wesley P. Chan

  2. Disney Research, Los Angeles, CA, USA

    Matthew K. X. J. Pan

  3. Faculty of Engineering, Monash University, Melbourne, VIC, Australia

    Elizabeth A. Croft

  4. Department of Information Science and Technology, University of Tokyo, Tokyo, Japan

    Masayuki Inaba

Authors
  1. Wesley P. Chan
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  2. Matthew K. X. J. Pan
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  3. Elizabeth A. Croft
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  4. Masayuki Inaba
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Correspondence to Wesley P. Chan.

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The user study documented in this paper was approved by the University of British Columbia Behavioural Research Ethics Board (H10-00503).

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Informed consent was obtained from all participants prior to data collection.

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Chan, W.P., Pan, M.K.X.J., Croft, E.A. et al. An Affordance and Distance Minimization Based Method for Computing Object Orientations for Robot Human Handovers. Int J of Soc Robotics 12, 143–162 (2020). https://doi.org/10.1007/s12369-019-00546-7

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