single-rb.php

JRM Vol.26 No.5 pp. 580-591
doi: 10.20965/jrm.2014.p0580
(2014)

Paper:

Effects of Haptic and 3D Audio Feedback on Operator Performance and Workload for Quadrotor UAVs in Indoor Environments

Robert M. Philbrick*,** and Mark B. Colton**

*MathWorks, 3 Apple Hill Drive Natick, MA 01760, USA

**Department of Mechanical Engineering, Brigham Young University, 435 CTB, Provo, UT 84602, USA

Received:
January 26, 2014
Accepted:
July 23, 2014
Published:
October 20, 2014
Keywords:
unmanned aerial vehicles, haptics, force feedback, 3D audio, multimodal interaction
Abstract
Haptic and audio 3D feedback
Unmanned aerial vehicles (UAVs) have many potential applications in indoor environments. However, limited visual feedback makes it difficult to pilot UAVs in cluttered and enclosed spaces. Haptic feedback combined with visual feedback has been shown to reduce the number of collisions of UAVs in indoor environments, but has generally resulted in an increase in the mental workload of the operator. This paper investigates the potential of combining novel haptic and 3D audio feedback to provide additional information to operators of UAVs to improve performance and reduce workload. Two haptic feedback and two 3D audio feedback algorithms are presented and tested in a simulation-based human subject experiment. Operator workload is quantified using standard measures and a novel application of behavioral entropy. Experimental results indicate that 3D haptic feedback improved UAV pilot performance. Pilot workload was also improved for one of the haptic algorithms in one of the control directions (lateral). The 3D audio feedback algorithms investigated in this study neither improved nor degraded pilot performance.
Cite this article as:
R. Philbrick and M. Colton, “Effects of Haptic and 3D Audio Feedback on Operator Performance and Workload for Quadrotor UAVs in Indoor Environments,” J. Robot. Mechatron., Vol.26 No.5, pp. 580-591, 2014.
Data files:
References
  1. [1] A. M. Brandt and M. B. Colton, “Haptic collision avoidance for a remotely operated quadrotor UAV in indoor environments,” In Proc. IEEE Int Systems Man and Cybernetics (SMC) Conf., pp. 2724-2731, 2010.
  2. [2] T. M. Lam, H.W. Boschloo, M. Mulder, M. M. v. Paassen, and F. C. T. v. d. Helm, “Effect of haptic feedback in a trajectory following task with an unmanned aerial vehicle,” In Proc. IEEE Int. Systems, Man and Cybernetics Conf, Vol.3, pp. 2500-2506, 2004.
  3. [3] T. M. Lam, M. Mulder, and M. M. v. Paassen, “Haptic interface in UAV tele-operation using force-stiffness feedback,” In Proc. IEEE Int. Conf. Systems,Man and Cybernetics (SMC 2009), pp. 835-840, 2009.
  4. [4] E. C. Haas, “Emerging Multimodal Technology,” Professional Safety: J. of the American Society of Safety Engineers, pp. 32-38, December 2007.
  5. [5] S. De Stigter, M. Mulder, and M. v. Paassen, “Design and Evaluation of a Haptic Flight Director,” J. of Guidance, Control, and Dynamics, Vol.30, No.1, pp. 35-46, 2007.
  6. [6] T. Nojima and K. Funabiki, “Cockpit display using tactile sensation,” In Eurohaptics Conference 2005 and Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems 2005, World Haptics 2005, First Joint, pp. 501-502, March 2005.
  7. [7] J. B. F. v. Erp, E. L. Groen, J. E. Bos, and H. A. H. C. v. Veen, “A Tactile Cockpit Instrument Supports the Control of Self-Motion During Spatial Disorientation,” Human Factors: The J. of the Human Factors and Ergonomics Society, Vol.48, No.2, pp. 219-228, 2006.
  8. [8] J. D. Lee, J. D. Hoffman, and E. Hayes, “Collision warning design to mitigate driver distraction,” In Proc. of the SIGCHI Conf. on Human factors in computing systems (CHI’04), pp. 65-72, New York, NY, USA, 2004.
  9. [9] R. S. Bolia, W. R. D’Angelo, and R. L. McKinley, “Aurally Aided Visual Search in Three-Dimensional Space,” Human Factors: The J. of the Human Factors and Ergonomics Society, Vol.41, No.4, pp. 664-669, 1999.
  10. [10] D. V. Gunn, J. S. Warm, W. T. Nelson, R. S. Bolia, D. A. Schumsky, and K. J. Corcoran, “Target Acquisition With UAVs: Vigilance Displays and Advanced Cuing Interfaces,” Human Factors: The J. of the Human Factors and Ergonomics Society, Vol.47, No.3, pp. 488-497, 2005.
  11. [11] H. D. Graham, “Effect of Auditory Peripheral Displays On Unmanned Aerial Vehicle Operator Performance,” Master’s thesis, United States Air Force Academy, 2006.
  12. [12] I. Maza, F. Caballero, R. Molina, N. Pena, and A. Ollero, “Multimodal Interface Technologies for UAV Ground Control Stations – A Comparative Analysis,” J. of Intelligent & Robotic Systems, Vol.57, pp. 371-391, 2010.
  13. [13] W. Yu and S. Brewster, “Evaluation of multimodal graphs for blind people,” Universal Access in the Information Society, Vol.2, pp. 105-124, 2003. DOI: 10.1007/s10209-002-0042-6.
  14. [14] E. Haas and C. Stachowiak, “Multimodal displays to enhance human robot interaction on-the-move,” In Proc. of the 2007 Workshop on Performance Metrics for Intelligent Systems (PerMIS’07), pp. 135-140, New York, NY, USA, 2007.
  15. [15] W. Chou and T. Wang, “The design of multimodal human-machine interface for teleoperation,” In Proc. IEEE Int Systems, Man, and Cybernetics Conf., Vol.5, pp. 3187-3192, 2001.
  16. [16] S. Stramigioli, R. Mahony, and P. Corke, “A novel approach to haptic tele-operation of aerial robot vehicles,” In Proc. IEEE Int. Robotics and Automation (ICRA) Conf., pp. 5302-5308, 2010.
  17. [17] S. Grzonka, G. Grisetti, andW. Burgard, “Towards a navigation system for autonomous indoor flying,” IEEE Int. Conf. on In Robotics and Automation 2009 (ICRA’09), pp. 2878-2883, May 2009.
  18. [18] H. Huang, G. Hoffmann, S. Waslander, and C. Tomlin, “Aerodynamics and control of autonomous quadrotor helicopters in aggressive maneuvering,” IEEE Int. Conf. on Robotics and Automation 2009 (ICRA’09), pp. 3277-3282, May 2009.
  19. [19] R. Leishman, J. Macdonald, T. McLain, and R. Beard, “Relative navigation and control of a hexacopter,” 2012 IEEE Int. Conf. on Robotics and Automation (ICRA), pp. 4937-4942, May 2012.
  20. [20] R. Leishman, J. Macdonald, S. Quebe, J. Ferrin, R. Beard, and T. McLain, “Utilizing an improved rotorcraft dynamic model in state estimation,” 2011 IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS), pp. 5173-5178, Sep. 2011.
  21. [21] V. Balas and M. Balas, “Driver Assisting by Inverse Time to Collision,” In Automation Congress 2006 (WAC’06)World, pp. 1-6, July 2006.
  22. [22] A. M. Brandt, “Haptic Collision Avoidance for a Remotely Operated Quadrotor UAV in Indoor Environments,” Master’s thesis, Brigham Young University, December 2009.
  23. [23] T.M. Lam,M.Mulder, and M. M. v. Paassen, “Haptic Feedback for UAV Tele-operation – Force offset and spring load modification,” Proc. IEEE Int. Conf. Systems, Man and Cybernetics (SMC’06), Vol.2, pp. 1618-1623, 2006.
  24. [24] M. A. Goodrich, E. R. Boer, J.W. Crandall, R. W. Ricks, and M. L. Quigley, “Behavioral Entropy in Human-Robot Interaction,” Proc. of PERMIS, Gaithersburg, Maryland, Aug. 24-26 2004.
  25. [25] R. W. Beard, “Quadrotor Dynamics and Control,” Brigham Young University, February 2008.
  26. [26] S. G. Hart and L. E. Staveland, “Development of NASA-TLX (Task Load Index): Results of empirical and theoretical research,” Human mental workload, Vol.1, No.11, pp. 139-183, 1988.
  27. [27] W. Navidi, “Statistics for Engineers and Scientists,” McGraw-Hill, 2nd edition, 2006.

*This site is desgined based on HTML5 and CSS3 for modern browsers, e.g. Chrome, Firefox, Safari, Edge, Opera.

Last updated on Apr. 19, 2024