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Testing & Validation Evaluating Mobility Performance of - - PowerPoint PPT Presentation

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Modeling & Simulation, Testing & Validation Evaluating Mobility Performance of Unmanned Ground Vehicles Michael P. Cole 1 Cory M. Crean 1 David J. Gorsich, PhD 1 Paramsothy Jayakumar, PhD 1 Abhinandan Jain, PhD 2 Tulga Ersal, PhD 3 1. US

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SLIDE 1

Modeling & Simulation, Testing & Validation

Evaluating Mobility Performance of Unmanned Ground Vehicles

Michael P. Cole1 Cory M. Crean1 David J. Gorsich, PhD1 Paramsothy Jayakumar, PhD1 Abhinandan Jain, PhD2 Tulga Ersal, PhD3

  • 1. US Army TARDEC 2. NASA Jet Propulsion Lab 3. University of Michigan

8/9/2018 UNCLASSIFIED: Distribution Statement A. Approved for public release; distribution is unlimited.

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SLIDE 2

Modeling & Simulation, Testing & Validation

Motivation

  • Military is highly interested in autonomy-enabled systems
  • Army currently uses NATO Reference Mobility Model

(NRMM) to evaluate vehicle mobility both on & off-road [1]

– Shortcoming: cannot evaluate UGV technologies such as autonomy, remote control with latency, ABS, traction control, etc.

  • Task: How to evaluate unmanned ground vehicle (UGV)

mobility performance in simulation?

8/9/2018 UNCLASSIFIED: Distribution Statement A. Approved for public release; distribution is unlimited.

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SLIDE 3

Modeling & Simulation, Testing & Validation Notional Relationship for Teleoperation

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SLIDE 4

Modeling & Simulation, Testing & Validation

Background

  • Years of research in field of teleoperation

– Undersea robots [2], ground robots [3-6], manipulators [7-10], vehicles [12-13]

  • Literature review highlighted lack of research at high

speeds (>25 mph) over range of latencies [12-14]

  • Developed testbed for UGV simulations
  • Performed baseline experiment using testbed:

teleoperation of Polaris MRZR 4 military vehicle

8/9/2018 UNCLASSIFIED: Distribution Statement A. Approved for public release; distribution is unlimited.

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SLIDE 5

Modeling & Simulation, Testing & Validation

Simulation Environment

  • JPL Rover Analysis Modeling & Simulation (ROAMS) [15]

– High fidelity dynamics engine – Latency injection – User input via steering wheel & pedals

Teleoperation Schematic Driver Visual Feedback

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User

Time Delay x(t – 𝜐(t))

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SLIDE 6

Modeling & Simulation, Testing & Validation

UGV Modes of Teleoperation

  • Pure teleoperation

– No driver aids – Latency: 0 to 1000ms by 200 ms

  • Enhanced teleoperation [13]

– Model free predictor – First order time delay system – Latency: 0 to 1000ms by 200 ms

Teleoperation Predictor Schematic [13]

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SLIDE 7

Modeling & Simulation, Testing & Validation

Participants and Test Procedure

Participants

  • Internal research team, 7 users
  • Little to no prior experience

using vehicle simulators

Test Procedure

  • Task: drive along centerline of curvy roadway
  • Guidance: maximize speed while minimizing path deviations
  • Training phase prior to testing phase
  • Run failure criteria

– Two wheel lift off – Drive off roadway for >5 seconds

Course Layout in ROAMS

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SLIDE 8

Modeling & Simulation, Testing & Validation

Simulation Results

  • As latency increases, average speed decreases and RMS

error increases.

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SLIDE 9

Modeling & Simulation, Testing & Validation Performance Effects of Training Phase

Post training, drivers achieved higher average speeds and higher RMS error (path deviation). Drove more aggressively.

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SLIDE 10

Modeling & Simulation, Testing & Validation Enhanced Teleoperation Performance

Enabling predictor increased performance. Statistically significant increase in average speed. Statically significant decrease in RMS error.

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SLIDE 11

Modeling & Simulation, Testing & Validation Mobility-Latency Relationship

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  • Overlaid TARDEC teleoperation simulation results

– 3 different vehicles – 3 different path following scenarios

  • Exponential regression used to develop functional relationship
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SLIDE 12

Modeling & Simulation, Testing & Validation

Conclusions

  • Mobility performance worsens with increased latency.
  • Functional relationship provides capability to predict

teleoperation mobility performance for path following scenarios.

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SLIDE 13

Modeling & Simulation, Testing & Validation

Future Work

  • Investigating autonomy-enabled systems
  • Semi & Full autonomy

– Human/Machine collaboration – Waypoint following – MPC-based autonomy

  • Soft soil terrains

– Sand, grass, mud

  • V&V using test data

8/9/2018 UNCLASSIFIED: Distribution Statement A. Approved for public release; distribution is unlimited.

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SLIDE 14

Modeling & Simulation, Testing & Validation

8/9/2018 UNCLASSIFIED: Distribution Statement A. Approved for public release; distribution is unlimited.

Acknowledgements This research was carried out in part at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration.

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SLIDE 15

Modeling & Simulation, Testing & Validation

References

1.

  • D. Ahlvin and P. Haley, "NATO Reference Mobility Model Edition II, NRMM II User’s Guide," U.S. Army

Waterways Experiment Station, Corps of Engineers, Vicksburg, MS, Technical Report Number GL-92-19, 1992. 2.

  • C. Bulich, A. Klein, R. Watson, and C. Kitts, "Characterization of delay-induced piloting instability for the triton

undersea robot," 2004 IEEE Aerospace Conference, Big Sky, MT, United States, vol. 1, pp. 409-423, 2004. 3.

  • J. P. Luck, P. L. McDermott, L. Allender, and D. C. Russell, "An investigation of real world control of robotic

assets under communication latency," 2006 ACM Conference on Human-Robot Interaction, Salt Lake City, Utah, United States, vol. 2006, pp. 202-209, 2006. 4.

  • F. Penizzotto, S. Garcia, E. Slawinski, and V. Mut, "Delayed Bilateral Teleoperation of Wheeled Robots

including a Command Metric," Mathematical Problems in Engineering, pp. 460476 (13 pp.), 2015. 5.

  • E. Slawinski, V. A. Mut, P. Fiorini, and L. R. Salinas, "Quantitative Absolute Transparency for Bilateral

Teleoperation of Mobile Robots," IEEE Transactions on Systems, Man and Cybernetics, Part A (Systems and Humans), vol. 42, no. 2, pp. 430-42, 2012. 6.

  • J. Storms, K. Chen, and D. Tilbury, "A shared control method for obstacle avoidance with mobile robots and its

interaction with communication delay " The International Journal of Robotics Research, vol. 36, no. 5-7, pp. 820-839 2017. 7.

  • Z. B. Tamas Heidegger, "Extreme Telesurgery," INTECH, Croatia, 2010.

8.

  • A. K. Bejczy, W. S. Kim, and S. C. Venema, "The phantom robot: predictive displays for teleoperation with time

delay," IEEE International Conference on Robotics and Automation, Los Alamitos, CA, USA, pp. 546-51, 1990. 9.

  • J. C. Lane, C. R. Carignan, B. R. Sullivan, D. L. Akin, T. Hunt, and R. Cohen, "Effects of time delay on telerobotic

control of neutral buoyancy vehicles," 2002 IEEE International Conference on Robotics and Automation, Piscataway, NJ, USA, vol. 3, pp. 2874-9, 2002.

8/9/2018 UNCLASSIFIED: Distribution Statement A. Approved for public release; distribution is unlimited.

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Modeling & Simulation, Testing & Validation

References

  • 10. W. R. Ferrell, "Remote manipulation with transmission delay," IEEE Transactions on Human Factors in

Electronics, vol. HFE-6, no. 1, pp. 24-32, 1965.

  • 11. Avatar Teleopeation [Online], available:

/www.nrec.ri.cmu.edu/projects/long_distance_teleoperation_avatar/.

  • 12. J. Davis, C. Smyth, and K. McDowell, "The effects of time lag on driving performance and a possible

mitigation," IEEE Transactions on Robotics, vol. 26, no. 3, pp. 590-593, 2010.

  • 13. Y. Zheng, M. J. Brudnak, P. Jayakumar, J. L. Stein, and T. Ersal, "An Experimental Evaluation of a Model-Free

Predictor Framework in Teleoperated Vehicles," 13th IFAC Workshop on Time Delay Systems, 2016.

  • 14. T. T. Vong, G. A. Haas, and C. L. Henry, "NATO Reference Mobility Model (NRMM) Modeling of the DEMO III

Experimental Unmanned, Ground Vehicle (XUV)," Army Research Laboratory, ARL-MR-435, 1999.

  • 15. A. Jain, J. Guineau, C. Lim, W. Lincoln, M. Pomerantz, G. Sohl, and R. Steele, "ROAMS: Planetary surface rover

simulation environment," International Symposium on Artificial Intelligence, Robotics and Automation in Space, Nara, Japan, 2003.

8/9/2018 UNCLASSIFIED: Distribution Statement A. Approved for public release; distribution is unlimited.