skip to main content
research-article
Open Access

Toward a framework for levels of robot autonomy in human-robot interaction

Published:10 July 2014Publication History
Skip Abstract Section

Abstract

Autonomy is a critical construct related to human-robot interaction (HRI) and varies widely across robot platforms. Levels of robot autonomy (LORA), ranging from teleoperation to fully autonomous systems, influence the way in which humans and robots interact with one another. Thus, there is a need to understand HRI by identifying variables that influence---and are influenced by---robot autonomy. Our overarching goal is to develop a framework for LORA in HRI. To reach this goal, our framework draws links between HRI and human-automation interaction, a field with a long history of studying and understanding human-related variables. The construct of autonomy is reviewed and redefined within the context of HRI. Additionally, this framework proposes a process for determining a robot's autonomy level by categorizing autonomy along a 10-point taxonomy. The framework is intended to be treated as a guideline for determining autonomy, categorizing the LORA along a qualitative taxonomy and considering HRI variables (e.g., acceptance, situation awareness, reliability) that may be influenced by the LORA.

References

  1. Alami, R., Chatila, R., Fleury, S., Ghallab, M., & Ingrand, F. (1998). An architecture for autonomy. International Journal of Robotics Research, 17(4), 315--337.Google ScholarGoogle ScholarCross RefCross Ref
  2. Arkin, R. C. (1998). Behavior Based Robotics. Boston: MIT Press. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. Baker, M., & Yanco, H. A. (2004). Autonomy mode suggestions for improving human-robot interaction. In Proceedings of the IEEE Conference on Systems, Man, and Cybernetics, 3, 2948--2953.Google ScholarGoogle ScholarCross RefCross Ref
  4. Beer, J. M., Fisk. A. D., & Rogers, W. A. (2012). Toward a psychological framework for levels of robot autonomy in human-robot interaction. Technical Report HFA-TR-1204, Georgia Institute of Technology. https://smartech.gatech.edu.Google ScholarGoogle Scholar
  5. Bekey, G. A. (2005). Autonomous robots: From biological inspiration to implementation and control. Cambridge, MA: The MIT Press. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. Breazeal, C. (2003). Emotion and sociable humanoid robots. International Journal of Human Computer Interaction, 59, 119--115. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. Breazeal, C. (2005). Socially intelligent robots. Interactions, 12(2), 19--22. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. Broadbent, E., Stafford, R. & MacDonald, B. (2009). Acceptance of healthcare robots for the older population: Review and future directions. International Journal of Social Robotics, 1(4), 319--330.Google ScholarGoogle ScholarCross RefCross Ref
  9. Brooks, R. A. (2002). It's 2001 already. Flesh and machines: How robots will change us (63--98). New York, NY: Vintage Books, Random House Inc.Google ScholarGoogle Scholar
  10. Bruemmer, D. J., Few, D. A., Boring, R. L., Marble, J. L., Walton, M. C., & Nielsen, C. W. (2005). Shared understanding for collaborative control. In Proceedings of the IEEE Conference on Systems, Man, and Cybernetics, 35(4), 494--504. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. Carlson, J., Murphy, R. R., & Nelson, A. (2004). Follow-up analysis of mobile robot failures. In Proceedings of the IEEE International Conference on Robotics and Automation, 5, 4987--4994. New Orleans, Louisiana.Google ScholarGoogle ScholarCross RefCross Ref
  12. Casper, J., & Murphy, R. (2003). Human-robot interactions during the robot-assisted urban search and rescue response at the World Trade Center. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, 33(3), 367--385. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. Cohen, M. S., Parasuraman, R., & Freeman, J. T. (1998). Trust in decision aids: A model and its training implications. In Proceedings of the International Command and Control Research and Technology Symposium, 1--37. Monterey, CA.Google ScholarGoogle Scholar
  14. Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319--340. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. Desai, M., Kaniarasu, P., Medvedev, M., Steinfeld, A., & Yanco (2013). Impact of robot failures and feedback on real-time trust. In Proceedings of the ACM/IEEE Conference on Human-Robot Interaction, 251--258. Tokyo, Japan. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. Desai, M., Medvedev, M., Vazquez, M., McSheehy, S., Gadea-Omelchenko, S., Bruggeman, C., Steinfeld, A., & Yanco, H. (2012). Effects of changing reliability on trust of robot systems. In Proceedings of the ACM/IEEE Conference on Human-Robot Interaction, 73--80. Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. Desai, M., Stubbs, K., Steinfeld, A., & Yanco, H. (2009). Creating trustworthy robots: Lessons and inspirations from automated systems. In Proceedings of the Society for the Study of Artificial Intelligence and the Simulation of Behaviour (AISB) Convention, New Frontiers in Human-Robot Interaction.Google ScholarGoogle Scholar
  18. Desai, M., & Yanco, H. A. (2005). Blending human and robot inputs for sliding scale autonomy. The IEEE International Workshop on Robot and Human Interactive Communication, 537--542. Nashville, Tennessee.Google ScholarGoogle ScholarCross RefCross Ref
  19. Dewar, R. D., & Dutton, J. E. (1996). The adoption of radical and incremental innovations---An empirical- analysis. Management Science, 32(11), 1422--1433. Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. Dzindolet, M. T., Peterson, S. A., Pomranky, R. A. Pierce, L. G., & Beck, H. P. (2003). The role of trust in automation reliance. International Journal of Computer Studies, 58, 697--718. Google ScholarGoogle ScholarDigital LibraryDigital Library
  21. Endsley, M. R. (1995). Toward a theory of situation awareness in dynamic systems. Human Factors, 37, 32--64.Google ScholarGoogle ScholarCross RefCross Ref
  22. Endsley, M. R. (2006). Situation awareness. In G. Savendy (Ed.), Handbook of human factors and ergonomics (3rd ed.), pp. 528--542. New York, NY: Wiley.Google ScholarGoogle Scholar
  23. Endsley, M. R., Bolte, B., & Jones, D. G. (2003). Designing for situation awareness: An approach to human-centered design. London: Taylor & Francis. Google ScholarGoogle ScholarDigital LibraryDigital Library
  24. Endsley, M. R., & Kaber, D. B. (1999). Level of automation effects on performance, situation awareness and workload in a dynamic control task. Ergonomics, 42(3), 462--492.Google ScholarGoogle ScholarCross RefCross Ref
  25. Endsley, M. R., & Kiris, E. O. (1995). The out-of-the-loop performance problem and level of control in automation. Human Factors, 37(2), 381--394.Google ScholarGoogle ScholarCross RefCross Ref
  26. Erikson, E. H. (1950). Childhood and society. New York, NY: W. W. Norton.Google ScholarGoogle Scholar
  27. Ezer, N., Fisk, A. D., & Rogers, W. A. (2009). Attitudinal and intentional acceptance of domestic robots by younger and older adults. Lecture Notes in Computer Science, 5615, 39--48. Google ScholarGoogle ScholarDigital LibraryDigital Library
  28. Feil-Seifer, D., Skinner, K., & Mataric, M. J. (2007). Benchmarks for evaluating socially assistive robotics. Interaction Studies, 8(3), 423--439.Google ScholarGoogle ScholarCross RefCross Ref
  29. Few, D., Smart, W. D., Bruemmer, D., & Neilsen, C. (2008). "Seamless autonomy": Removing autonomy level stratifications. In Proceedings of the Conference on Human System Interactions, 446--451. Kraków, Poland.Google ScholarGoogle Scholar
  30. Fong, T., Nourbakhsh, I., & Dautenhahn, K. (2003). A survey of socially interactive robots. Robotics and Autonomous Systems, 42, 143--166.Google ScholarGoogle ScholarCross RefCross Ref
  31. Franklin, S., & Graesser, A. (1996). Is it an agent, or just a program? A taxonomy for autonomous agents. In Proceedings of the Third International Workshop on Agent Theories, Architectures, and Languages, Intelligent Agents, 21--35. Budapest Hungary. Google ScholarGoogle ScholarDigital LibraryDigital Library
  32. Goodrich, M. A., & Olsen, D. R. (2003). Seven principles of efficient human robot interaction. In Proceedings of the IEEE International Conference on Systems, Man and Cybernetics, 1--5, 3943--3948.Google ScholarGoogle ScholarCross RefCross Ref
  33. Goodrich, M. A., & Schultz, A. C. (2007). Human-robot interaction: A survey. Foundations and Trends in Human-Computer Interaction, 1(3), 203--275. Google ScholarGoogle ScholarDigital LibraryDigital Library
  34. Gorman, J. C., Cook, N. J., & Winner, J. L. (2006). Measuring team situation awareness in decentralized command and control environments. Ergonomics, 49(12--13), 1312--1325.Google ScholarGoogle Scholar
  35. Green, S. G., Gavin, M. B., & Aimansmith, L. (1995). Assessing a multidimensional measure of radical technological innovation. IEEE Transactions on Engineering Management, 42(3), 203--214.Google ScholarGoogle ScholarCross RefCross Ref
  36. Groom, V., & Nass, C. (2007). Can robots be teammates? Benchmarks in human-robot teams. Psychological Benchmarks of Human-Robot Interaction: Special issue of Interaction Studies, 8(3), 483--500.Google ScholarGoogle Scholar
  37. Hancock, P. A., Billings, D. R., & Schaefer, K. E. (2011). Can you trust your robot? Ergonomics in Design, 19(3), 24--29.Google ScholarGoogle ScholarCross RefCross Ref
  38. Hearst, M. A. (1999). Mixed-initiative interaction: Trends and controversies. IEEE Intelligent Systems, 14(5), 14--23.Google ScholarGoogle ScholarDigital LibraryDigital Library
  39. Huang, H.-M, (2004). Autonomy levels for unmanned systems (ALFUS) framework volume I: Terminology version 1.1. In Proceedings of the National Institute of Standards and Technology (NISTSP), Gaithersburg, MD.Google ScholarGoogle Scholar
  40. Huang, H.-M, Messina, E. R., Wade, R. L., English, R. W, Novak, B., & Albus, J. S. (2004). Autonomy measures for robots. In Proceedings of the International Mechanical Engineering Congress (IMECE), 1--7. Anaheim, California.Google ScholarGoogle ScholarCross RefCross Ref
  41. Huang, H.-M, Pavek, K, Albus, J., & Messina, E. (2005). Autonomy levels for unmanned systems (ALFUS) framework: An update. In Proceedings of the SPIE Defense and Security Symposium, 5804, 439--448. Orlando, Florida.Google ScholarGoogle ScholarCross RefCross Ref
  42. Huang, H.-M, Pavek, K., Novak, B., Albus, J. S., & Messina, E. (2005). A framework for autonomy levels for unmanned systems (ALFUS). In Proceedings of the AUVSI's Unmanned Systems North America, 849--863. Baltimore, Maryland.Google ScholarGoogle ScholarCross RefCross Ref
  43. Huang, H.-M, Pavek, K., Ragon, M., Jones, J., Messina, E., & Albus, J. (2007). Characterizing unmanned system autonomy: Contextual autonomous capability and level of autonomy analyses. In Proceedings of the 2007 SPIE Defense and Security Symposium. Orlando, Florida..Google ScholarGoogle ScholarCross RefCross Ref
  44. Johnson, M., Bradshaw, J. M., Feltovich, P. J., Jonker, C., Sierhuis, M., & van Riemsdijk, B. (2010). Toward Coactivity. In Proceedings of the ACM/IEEE Conference on Human-Robot Interaction, 101--102. Osaka, Japan. Google ScholarGoogle ScholarDigital LibraryDigital Library
  45. Kaber, D. B., Onal, E., & Endsley, M. R. (2000). Design of automation for telerobots and the effect on performance, operator situation awareness, and subjective workload. Human Factors and Ergonomics in Manufacturing, 10(4), 409--430.Google ScholarGoogle ScholarCross RefCross Ref
  46. Kaber, D. B., Wright, M. C., & Sheik-Nainar, M. A. (2006). Investigation of multi-modal interface features for adaptive automation of a human-robot system. International Journal of Human-Computer Studies, 64, 527--540. Google ScholarGoogle ScholarDigital LibraryDigital Library
  47. Kant, I. (1967). Kant: Philosophical Correspondence, 1795--99. (A. Zweig, Ed.). Chicago, IL: University of Chicago Press.Google ScholarGoogle Scholar
  48. Khan, Z. (1998). Attitude towards intelligent service robots. Numerical Analysis and Computer Science. Technical Report (TRITA-NA-P9821). Stockholm Sweden: Royal Institute of Technology.Google ScholarGoogle Scholar
  49. Kim, T., & Hinds, P. (2006). Who should I blame? Effects of autonomy and transparency on attributions in human-robot interaction. In Proceedings of the IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN), 80--85. Hatfield, United Kingdom.Google ScholarGoogle ScholarCross RefCross Ref
  50. Lee, J. D., & See, K. A. (2004). Trust in automation: Designing for appropriate reliance. Human Factors, 46, 50--80.Google ScholarGoogle ScholarCross RefCross Ref
  51. Lee, M. K. & Takayama, L. (2011). "Now I have a body": Uses and social norms of mobile remote presence in the workplace. In Proceedings of the ACM Conference on Human Factors in Computing Systems (SIGCHI), 33--42. Vancouver, British Columbia. Google ScholarGoogle ScholarDigital LibraryDigital Library
  52. Lewis, M., Wang, H., Chien, S. Y., Velagapudi, P., Scerri, P., & Sycara, K. (2010). Choosing autonomy modes for multi-robot search. Human Factors, 52(2), 225--233.Google ScholarGoogle ScholarCross RefCross Ref
  53. Madhavan, P., & Wiegmann, D. A. (2007). Similarities and differences between human-human and human-automation trust: An integrative review. Theoretical Issues in Ergonomics, 8(4), 277--301.Google ScholarGoogle ScholarCross RefCross Ref
  54. Milgram, P., Rastogi, A., & Grodski, J. J. (1995). Telerobotic control using augmented reality. IEEE International Workshop on Robot and Human Communication, 21--29. Tokyo, Japan.Google ScholarGoogle ScholarCross RefCross Ref
  55. Murphy, R. (2000). Introduction to AI Robotics (pp. 1--40). Cambridge, MA: The MIT Press. Google ScholarGoogle ScholarDigital LibraryDigital Library
  56. Murphy, R. & Schreckenghost, D. (2013). Survey of metrics for human-robot interaction. In Proceedings of the ACM/IEEE Conference on Human-Robot Interaction, 197--198. Tokyo, Japan. Google ScholarGoogle ScholarDigital LibraryDigital Library
  57. Mutlu, B. & Forlizzi, J. (2008). Robots in organizations: Workflow, social, and environmental factors in human-robot interaction. In Proceedings of the ACM/IEEE Conference on Human-Robot Interaction, 239--248. Amsterdam, Netherlands. Google ScholarGoogle ScholarDigital LibraryDigital Library
  58. Nass, C., & Moon, Y. (2000). Machines and mindlessness: Social responses to computers. Journal of Social Issues, 56(1), 81--103.Google ScholarGoogle ScholarCross RefCross Ref
  59. Nass, C., Fogg, B. J., & Moon, Y. (1996). Can computers be teammates? International Journal of Human-Computer Studies, 45(6), 669--678. Google ScholarGoogle ScholarDigital LibraryDigital Library
  60. Nass, C., Moon, Y., Fogg, B. J., & Reeves, B. (1995). Can computer personalities be human personalities? International Journal of Human-Computer Studies, 43(2), 223--239. Google ScholarGoogle ScholarDigital LibraryDigital Library
  61. Nass, C., Steuer, J., Henriksen, L., & Dryer, D. C. (1994). Machines, social attributions, and ethopoeia: Performance assessments of computers subsequent to 'self-' or 'other-' evaluations. International Journal of Human-Computer Studies, 40(3), 543--559. Google ScholarGoogle ScholarDigital LibraryDigital Library
  62. Olsen, D. R., & Goodrich, M. A. (2003). Metrics for evaluating human-robot interactions. In Proceedings of NIST Performance Metrics for Intelligent Systems Workshop. Gaithersburg, Maryland.Google ScholarGoogle Scholar
  63. Parasuraman, R., & Riley, V. (1997). Humans and automation: Use, misuse, disuse, abuse. Human Factors, 39(2), 230--253.Google ScholarGoogle ScholarCross RefCross Ref
  64. Parasuraman, R., & Wickens, C. D. (2008). Humans: Still vital after all these years of automation. Human Factors, 50(3), 511--520.Google ScholarGoogle ScholarCross RefCross Ref
  65. Parasuraman, R., Sheridan, T. B., & Wickens, C. D. (2000). A model for types and levels of human interaction with automation. IEEE Transactions on Systems Man and Cybernetics Part A: Systems and Humans, 30(3), 286--297. Google ScholarGoogle ScholarDigital LibraryDigital Library
  66. Parasuraman, R., Sheridan, T. B., & Wickens, C. D. (2008). Situation awareness, mental workload, and trust in automation: Viable, empirically supported cognitive engineering constructs. Journal of Cognitive Engineering and Decision Making, 2(2), 140--160.Google ScholarGoogle ScholarCross RefCross Ref
  67. Piaget, J. (1932). The Moral Judgment of a Child. Glencoe, IL: The Free Press.Google ScholarGoogle Scholar
  68. Prakash, A., Beer, J. M., Deyle, T., Smarr, C.-A., Che, T. L., Mitzner, T. L., Kemp, D. C., & Rogers, W. A. (2013). Older adults' medication management in the home: How can robots help? In Proceedings of the ACM/IEEE Conference on Human-Robot Interaction, 283--290. Tokyo, Japan. Google ScholarGoogle ScholarDigital LibraryDigital Library
  69. Rosen, C. A. & Nilsson, N. J (1966). Application Of Intelligent Automata to Reconnaissance. Technical Report. Menlo Park, CA: Stanford Research Institute.Google ScholarGoogle Scholar
  70. Riley, J. M., & Endsley, M. R. (2004). The hunt for situation awareness: Human-robot interaction in search and rescue. In Proceedings of the Human Factors and Ergonomics Society 48th Annual Meeting, 693--697. New Orleans, Louisiana.Google ScholarGoogle ScholarCross RefCross Ref
  71. Russell, S. J., & Norvig, P. (2003). Artificial intelligence: A modern approach (2nd ed.). Upper Saddle River, NJ: Pearson Education, Inc. Google ScholarGoogle ScholarDigital LibraryDigital Library
  72. Scholtz, J. (2002a). Theory and evaluation of human-robot interactions. In Proceedings of the IEEE International Conference on System Sciences. Waikoloa Village, Hawaii. Google ScholarGoogle ScholarDigital LibraryDigital Library
  73. Scholtz, J. (2002b). Human-robot interactions: Creating synergistic cyber forces. In Proceedings from the NRL Workshop on Multi-Robot Systems: From Swarms to Intelligent Automata. 177--184. Washington, DC.Google ScholarGoogle ScholarCross RefCross Ref
  74. Scholtz, J., Antonishek, B., & Young, J. (2004). Evaluation of a human-robot interface: Development of a situational awareness methodology. In Proceedings of the International Conference on System Sciences, 1--9. Waikoloa Village, Hawaii. Google ScholarGoogle ScholarDigital LibraryDigital Library
  75. Sheridan, T. B., & Verplank, W. L. (1978). Human and computer control of undersea teleoperators. Man-Machine Systems Laboratory Report. Cambridge, MA: MIT.Google ScholarGoogle Scholar
  76. Skinner, B. F. (1978). Reflection on behaviorism and society. Englewood Cliffs, NJ: Prentice-Hall.Google ScholarGoogle Scholar
  77. Steinfeld, A., Fong, T., Kaber, D., Lewis, M., Scholtz, J., Schultz, A., & Goodrich, M. (2006). Common metrics for human-robot interaction. In Proceedings of Human-Robot Interaction Conference, 33--40. Salt Lake City, Utah. Google ScholarGoogle ScholarDigital LibraryDigital Library
  78. Stubbs, K., Hinds, P., & Wettergreen, D. (2007). Autonomy and common ground in human-robot interaction: A field study. IEEE Intelligent Systems: Special Issue on Interacting with Autonomy, 22(2), 42--50. Google ScholarGoogle ScholarDigital LibraryDigital Library
  79. Takayama, L., Marder-Eppstein, E., Harris, H., & Beer, J. M. (2011). Assisted driving of a mobile remote presence system: System design and controlled user evaluation. In Proceedings of the International Conference on Robotics and Automation (ICRA), 1883-1889. Shanghai, CN.Google ScholarGoogle ScholarCross RefCross Ref
  80. Tarn, T.-J., Zi, N., Guo, C., & Bejczy, A. K. (1995). Function-based control sharing for robotics systems. In Proceedings on IEEE International Conference on Intelligent Robots and Systems, 3, 1--6. Pittsburgh, Pennsylvania. Google ScholarGoogle ScholarDigital LibraryDigital Library
  81. Thrun, S. (2004). Toward a framework for human-robot interaction. Human-Computer Interaction, 19(1--2), 9--24. &2_2 Google ScholarGoogle ScholarDigital LibraryDigital Library
  82. Tiwari, P., Warren, J., Day, K. J., & MacDonald, B. (2009). Some non-technology implications for wider application of robots to assist older people. In Proceedings of the Conference and Exhibition of Health Informatics. New Zealand.Google ScholarGoogle Scholar
  83. Tsui, K. M., Desai, M., Yanco, H., & Uhlik, C. (2011). Exploring use cases for telepresence robots. In Proceedings of the ACM/IEEE Conference on Human-Robot Interaction, 11--18. Lausanne, Switzerland. Google ScholarGoogle ScholarDigital LibraryDigital Library
  84. Tsang, P. S. & Vidulich, M. A. (2006). Mental workload and situation awareness. In G. Savendy (Ed.), Handbook of Human Factors and Ergonomics (3rd ed., pp. 243--268). New York, NY: Wiley.Google ScholarGoogle Scholar
  85. Urdiales, C., Poncela, A., Sanchez-Tato, I., Galluppi, F., Olivetti, M., & Sandoval, F. (2007). Efficiency based reactive shared control for collaborative human/robot navigation. In Proceedings from the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 3586--3591. San Diego, California.Google ScholarGoogle ScholarCross RefCross Ref
  86. Wellman, H. (1992). The Child's Theory of Mind. Boston, MA: MIT Press.Google ScholarGoogle Scholar
  87. Wooldridge, M., & Jennings, N. R. (1995). Intelligent agents: Theory and practice. Knowledge Engineering Review, 10, 115--152.Google ScholarGoogle ScholarCross RefCross Ref
  88. Yanco, H. & Drury, J. (2004). Classifying human-robot interaction: An updated taxonomy. In Proceedings of the IEEE International Conference on Systems, Man and Cybernetics, 3, 2841--2846. Hague, Netherlands.Google ScholarGoogle ScholarCross RefCross Ref
  89. Young, J., Hawkins, R., Sharlin, E., and Igarashi, T. (2009). Toward acceptable domestic robots: Applying insights from social psychology. International Journal of Social Robotics, 1(1), 95--108.Google ScholarGoogle ScholarCross RefCross Ref

Index Terms

  1. Toward a framework for levels of robot autonomy in human-robot interaction
      Index terms have been assigned to the content through auto-classification.

      Recommendations

      Comments

      Login options

      Check if you have access through your login credentials or your institution to get full access on this article.

      Sign in

      Full Access

      PDF Format

      View or Download as a PDF file.

      PDF

      eReader

      View online with eReader.

      eReader