User Interfaces for Human-Robot Interaction in Field Robotics

Part of the Springer Tracts in Advanced Robotics book series (STAR, volume 128)


This chapter proposes thirty-two guidelines for pro-actively building a good human-robot user interface and illustrates them through case studies of two technological mature ImPACT Tough Robotics Challenge (TRC) systems: the cyber K9 and construction robot projects. A designer will likely have to build three notably different interfaces at different points in the development process: a diagnostic interface for developers to monitor and debug the robot using their expert knowledge, an end-user interface which is tailored to the tasks and decisions that operator and knowledge workers must execute, and an explicative interface to enable the public to visualize the important scientific achievements afforded by the robot system. The thirty-two guidelines are synthesized from the human-computer interaction, human-robot interaction, and computer supported coordinated work (CSCW) groups communities are clustered around four general categories: roles, layout appropriateness, the Four C’s (content, comparison,l coordination, color), and general interaction with, and through, the display.



This work was supported by Impulsing Paradigm Change through Disruptive Technologies (ImPACT) Tough Robotics Challenge program of Japan Science and Technology (JST) Agency.


  1. 1.
    Burke, J., Murphy, R.: Human-robot interaction in USAR technical search: Two heads are better than one. In: 13th IEEE International Workshop on Robot and Human Interactive Communication (RO-MAN), Conference Proceedings, pp. 307–312Google Scholar
  2. 2.
    Burns, C.M., Hajdukiewicz, J.: Ecological Interface Design. CRC Press, Boca Raton (2004)Google Scholar
  3. 3.
    Card, S., Moran, T.P., Newell, A.: The Psychology of Human Computer Interaction. Lawrence Erlbaum, Hillsdale (1983)Google Scholar
  4. 4.
    Casper, J.: Human-robot interactions during the robot-assisted urban search and rescue response at the world trade center, Thesis (2002)Google Scholar
  5. 5.
    Chung, H., Chu, S.L., North, C.: A comparison of two display models for collaborative sensemaking. In: Proceedings of the 2nd ACM International Symposium on Pervasive Displays. 2491577: ACM, Conference Proceedings, pp. 37–42Google Scholar
  6. 6.
    Cockburn, A., Karlson, A., Bederson, B.B.: A review of overview+detail, zooming, and focus+context interfaces. ACM Comput. Surv. 41(1), 1–31 (2009)CrossRefGoogle Scholar
  7. 7.
    Cooper, J.L., Goodrich, M.A.: Towards combining UAV and sensor operator roles in UAV-enabled visual search, pp. 351–358. 12–15 March 2008Google Scholar
  8. 8.
    Demir, I., Jarema, M., Westermann, D.: Visualizing the central tendency of ensembles of shapes, pp. 1–8 (2016)Google Scholar
  9. 9.
    Grudin, J: Partitioning digital worlds: focal and peripheral awareness in multiple monitor use. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. 365312: ACM, Conference Proceedings, pp. 458–465, old paper but establishes focal peripheryGoogle Scholar
  10. 10.
    Hutchings, D.R., Stasko, J., Czerwinski, M.: Distributed display environments. Interactions 12(6), 50–53 (2005) (seem interesting)Google Scholar
  11. 11.
    Hutchings, D.R., Stasko, J.: Consistency, multiple monitors, and multiple windows. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. 1240658: ACM, Conference Proceedings, pp. 211–214Google Scholar
  12. 12.
    Ishak, E.W., Feiner, S.: Content-aware layout. In: CHI ’07 Extended Abstracts on Human Factors in Computing Systems. 1241024: ACM, Conference Proceedings, pp. 2459–2464Google Scholar
  13. 13.
    Klein, G., Woods, D.D., Bradshaw, J.M., Hoffman, R.R., Feltovich, P.J.: Ten challenges for making automation a “team player” in joint human-agent activity. IEEE Intell. Syst. 19(6), 91–95 (2004)CrossRefGoogle Scholar
  14. 14.
    Klingenberg, C.: Visualizations in geometric morphometrics: How to read and how to make graphs showing shape changes. Hystrix 24, 1–10 (2013)Google Scholar
  15. 15.
    Lee, W., Ryu, H., Yang, G., Kim, H., Park, Y., Bang, S.: Design guidelines for map-based human-robot interfaces: a colocated workspace perspective. Int. J. Ind. Ergon. 37(7), 589–604 (2007)CrossRefGoogle Scholar
  16. 16.
    Lischke, L., Mayer, S., Wolf, K., Henze, N., Reiterer, H., Schmidt, A.: Screen arrangements and interaction areas for large display work places. In: Proceedings of the 5th ACM International Symposium on Pervasive Displays, pp. 228–234Google Scholar
  17. 17.
    Malmstrom, C., Zhang, Y., Pasquier, P., Schiphorst, T., Bartram, L.: Mocomp: a tool for comparative visualization between takes of motion capture data, pp. 1–8 (2016)Google Scholar
  18. 18.
    Marrinan, T., Leigh, J., Renambot, L., Forbes, A., Jones, S., Johnson, A.E.: Mixed presence collaboration using scalable visualizations in heterogeneous display spaces. In: Proceedings of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing. 2998346: ACM, Conference Proceedings, pp. 2236–2245Google Scholar
  19. 19.
    McKenney, M., Viswanadham, S.C., Littman, E.: The CMR model of moving regions, pp. 62–71 (2014)Google Scholar
  20. 20.
    Miller, G.: The magical number seven, plus or minus two: some limits on our capacity for processing information. Psychol. Rev. 63(2), 81–97 (1956)CrossRefGoogle Scholar
  21. 21.
    Murphy, R., Burke, J.: From remote tool to shared roles. IEEE Robot. Autom. Mag. (special issue on New Vistas and Challenges for Teleoperation) 15(4), 39–49 (2008)CrossRefGoogle Scholar
  22. 22.
    Murphy, R.R.: Disaster Robotics. MIT Press, Cambridge (2014)CrossRefGoogle Scholar
  23. 23.
    Murphy, R.R., Burke, J.L.: The safe human-robot ratio. In: Human-Robot Interactions in Future Military Operations. Ashgate Publishing Company, Brookfield, VT (2009)Google Scholar
  24. 24.
    Murphy, R.R., Pratt, K.S., Burke, J.: Crew roles and operational protocols for rotary-wing micro-UAVs in close urban environments. In: Proceedings of the 3rd ACM/IEEE Human-Robot Interaction, pp. 73–80 (2008)Google Scholar
  25. 25.
    Nielsen, J.: Enhancing the explanatory power of usability heuristics, pp. 152–158 (1994)Google Scholar
  26. 26.
    Nielsen, J.: Powers of 10: time scales in user experience (2009)Google Scholar
  27. 27.
    Nielsen, C.W., Goodrich, i.A., Ricks, R.W.: Ecological interfaces for improving mobile robot teleoperation. IEEE Trans. Robot. 23(5), 927–941 (2007)CrossRefGoogle Scholar
  28. 28.
    Pattison, T., Phillips, M.: View coordination architecture for information visualisation. In: Proceedings of the 2001 Asia-Pacific symposium on Information visualisation - Volume 9. 564061: Australian Computer Society, Inc., Conference Proceedings, pp. 165–169Google Scholar
  29. 29.
    Peer, S., Sharma, D.K., Ravindranath, K., Naidu, M.: Layout design of user interface components with multiple objectives. Yugosl. J. Oper. Res. 14(2), 171–192 (2004)MathSciNetCrossRefGoogle Scholar
  30. 30.
    Peschel, J.M., Murphy, R.R.: On the human-machine interaction of unmanned aerial system mission specialists. IEEE Trans. Hum.-Mach. Syst. 43(1), 53–62 (2013)CrossRefGoogle Scholar
  31. 31.
    Plumlee, M., Ware, C.: An evaluation of methods for linking 3d views. In: Proceedings of the 2003 Symposium on Interactive 3D Graphics. 641517: ACM, Conference Proceedings, pp. 193–201Google Scholar
  32. 32.
    Sears, A.L.: Layout appropriateness: guiding user interface design with simple task descriptions. Thesis, University of Maryland, 1993, advisor - Ben ShneidermanGoogle Scholar
  33. 33.
    Shneiderman, B.: Designing the User Interface: Strategies for Effective Human. Computer Interaction. Addison-Wesley (1998)Google Scholar
  34. 34.
    Tevs, A., Huang, Q., Wand, M., Seidel, H.-P., Guibas, L.: Relating shapes via geometric symmetries and regularities. ACM Trans. Graph. 33(4), 1–12 (2014)CrossRefGoogle Scholar
  35. 35.
    Truemper, J.M., Sheng, H., Hilgers, M.G., Hall, R.H., Kalliny, M., Tandon, B.: Usability in multiple monitor displays. SIGMIS Database 39(4), 74–89 (2008)CrossRefGoogle Scholar
  36. 36.
    Vicente, K.J.: Cognitive Work Analysis: Toward Safe, Productive, and Healthy Computer-Based Work. LEA Inc., Mahwah (1999)Google Scholar
  37. 37.
    Wang–Baldonado, M.Q., Woodruff, A., Kuchinsky, A.: Guidelines for using multiple views in information visualization. In: Proceedings of the Working Conference on Advanced Visual Interfaces. 345271: ACM, Conference Proceedings, pp. 110–119 (8 guidelines)Google Scholar
  38. 38.
    Wickens, C., Dixon, S., Chang, D.: Multiple resources and mental workload. Hum. Factors 50(3), 449–454 (2008)CrossRefGoogle Scholar

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© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Texas A&M UniversityCollege StationUSA
  2. 2.Tohoku UniversitySendaiJapan

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