The Mars Exploration Rover Surface Mobility Flight Software

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of the terrain comes from local plane fitting. our place in the spirit rover ......

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Published in 2006 IEEE Aerospace Conference Proceedings, March 2006, Big Sky, Montana, USA

The Mars Exploration Rover Surface Mobility Flight Software: Driving Ambition Jeffrey J. Biesiadecki and Mark W. Maimone Jet Propulsion Laboratory Pasadena, CA USA [email protected] [email protected] Abstract—

AUTONOMOUS G OAL S ELECTION

10

D EPLOYMENT R ESULTS

10

S OFTWARE V ERSIONS

11

7

C ONCLUSION

13

8

ACKNOWLEDGEMENTS

13

6 NASA’s Mars Exploration Rovers’ (MER) onboard Mobility Flight Software was designed to provide robust and flexible operation. The MER vehicles can be commanded directly, or given autonomous control over multiple aspects of mobility: which motions to drive, measurement of actual motion, terrain interpretation, even the selection of targets of interest (although this mode remains largely underused). Vehicle motion can be commanded using multiple layers of control: Motor Control, Direct Drive operations (Arc, Turn in Place), and Goal-based Driving (Goto Waypoint). Multiple layers of safety checks ensure vehicle performance: Command limits (command timeout, time of day limit, software enable, activity constraints), Reactive checks (e.g., motor current limit, vehicle tilt limit), and Predictive checks (e.g., Step, Tilt, Roughness hazards). From January 2004 through October 2005, Spirit accumulated over 5000 meters and Opportunity 6000 meters of odometry, often covering more than 100 meters in a single day. In this paper we describe the software that has driven these rovers more than a combined 11,000 meters over the Martian surface, including its design and implementation, and summarize current mobility performance results from Mars.

1. I NTRODUCTION

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2. MER F LIGHT S OFTWARE A RCHITECTURE

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4

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5

Driving Mode Directed Driving Visodom Blind Goto Waypoint Visodom Goto Waypoint Guarded Motion Guarded Visodom Autonav Autonav with Visodom

Terrain Assessment no no no no YES YES YES YES

Path Selection no no YES YES no no YES YES

Visual Odometry no YES no YES no YES no YES

Spirit 451 m 9% 410 m 8% 2196 m 46% 379 m 7% 36 m 1% 0m 0% 1315 m 27% 3m 0% 4798 m 100%

Opportunity 1973 m 33% 561 m 9% 1911 m 32% 121 m 2% 117 m 1% 0m 0% 1262 m 21% 0m 0% 5947 m 100%

Table 2. MER driving mode usage as of 15 August 2005, counting 573 sols for Spirit and 555 sols for Opportunity. (Distances are as measured onboard, and can be overestimates of actual distance traveled if wheels slip during non-Visodom drives. Only rover translation distances are reflected here; turn in place and single-wheel trench digging motions are not reported.)

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Figure 3. Illustration of Terrain Assessment and Path Selection. Red cells indicate unsafe areas around the large rock, yellow cells indicate traversable but rougher areas around the smaller rock, and green cells indicate safe and flat areas.

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Figure 5. Illustration of Goodness Map from Spirit’s Sol 107. Red areas indicate obstacles (typically a rock taller than 20cm at the center of the red blob), yellow/orange indicate traversable areas. Only information within a 5-meter radius is maintained in the onboard map.

Figure 4. Front HAZCAM showing a non-geometric hazard encountered by Opportunity on Sol 446: 50 meters of commanded driving resulted in only 2 meters progress, which you can see in the tracks leading up to Purgatory Ripple, in which Opportunity was mired for over a month. Although this was a “blind” or Directed drive, Opportunity might have gotten stuck even if GESTALT had been turned on because there were no geometric hazards to avoid, just loose terrain. Fortunately, Visual Odometry has been used ever since as a Slip Check to ensure we never command more than 5 meters of driving without a guarantee of motion; this new safety check helped out on Sol 603, when Visodom measured 44% slip while climbing a similar dune, and stopped the drive before getting further bogged down. Opportunity was able to back out easily during its next drive.

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Terrain Assessment

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[1] Khaled S. Ali, C Anthony Vanelli, Jeffery J. Biesiadecki, Mark W. Maimone, Yang Cheng, Miguel San Martin, and James W. Alexander. Attitude and position esimation on the Mars Exploration Rovers. In IEEE Conference on Systems, Man and Cybernetics, The Big Island, Hawaii, USA, October 2005.

8. ACKNOWLEDGEMENTS

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[2] P. Bellutta, R. Manduchi, L. Matthies, K. Owens, and A. Rankin. Terrain perception for demo iii. In Proc. Intelligent Vehicles Symposium, Dearborn, MI, October 2000. [3] Jeffrey Biesiadecki, Mark Maimone, and Jack Morrison. The Athena SDM rover: A testbed for Mars rover mobility. In International Symposium on Artificial Intelligence, Robotics, and Automation for Space (i-SAIRAS), Montreal, Canada, June 2001. http://robotics.jpl.nasa.gov/people/mwm/sdmmobility/. [4] Jeffrey J. Biesiadecki, Eric T. Baumgartner, Robert G. Bonitz, Brian K. Cooper, Frank R. Hartman, P. Christopher Leger, Mark W. Maimone, Scott A. Maxwell, Ashitey Trebi-Ollenu, Edward W. Tunstel, and John R. Wright. Mars Exploration Rover surface operations: Driving opportunity at meridiani planum. In IEEE Conference on Systems, Man and Cybernetics, The Big Island, Hawaii, USA, October 2005.

Jeffrey Biesiadecki has been a software engineer at NASA’s Jet Propulsion Laboratory since 1993, after completing his Master’s degree in Computer Science at the University of Illinois, UrbanaChampaign. He designed and implemented the core motor control and nonautonomous mobility flight software for the Mars Exploration Rovers, and is also one of the rover drivers for the Mars Exploration Rover ”Opportunity”, responsible for command sequences that tell the rover where to drive and how to operate its robotic arm on the surface of Mars.

[5] Jeffrey J. Biesiadecki, Chris Leger, and Mark W. Maimone. Tradeoffs between directed and autonomous driving on the mars exploration rovers. In International Symposium of Robotics Research, San Francisco, CA, USA, October 2005. [6] Yang Cheng, Mark Maimone, and Larry Matthies. Visual odometry on the Mars Exploration Rovers. In IEEE Conference on Systems, Man and Cybernetics, The Big Island, Hawaii, USA, October 2005. [7] Donald B. Gennery. Calibration and Orientation of Cameras in Computer Vision, chapter Least-Squares Camera Calibration Including Lens Distortion and Automatic Editing of Calibration Points, pages 123–136. Springer Verlag (A. Gruen and T. Huang, ed.), 2001.

Dr. Mark Maimone is a Navigation and Machine Vision researcher at the Jet Propulsion Laboratory. He earned his Ph.D. in Computer Science from the Computer Science Department of Carnegie Mellon University in 1996, and was then a Post-doctoral Research Associate at Carnegie Mellon’s Robotics Institute. Since starting at JPL in 1997, he has worked on the several Mars Rover research projects and a vision system for inspection of the Chornobyl reactor. As a member of the 2003 Mars Exploration Rover flight software team, Mark developed the vision and navigation subsystems for the MER vehicles. Mark is now part of the MER ground operations team and is developing the autonomous navigation software for the Mars Science Laboratory rover, NASA’s next Mars rover mission.

[8] Steven B. Goldberg, Mark W. Maimone, and Larry Matthies. Stereo vision and rover navigation software for planetary exploration. In IEEE Aerospace Conference, volume 5, pages 2025–2036, Big Sky, Montana, USA, March 2002. http://robotics.jpl.nasa.gov/people/mwm/visnavsw/. [9] M. Golombek and D. Rapp. Size-frequency distributions of rocks on Mars and Earth analog sites: Implications for future landed missions. Journal of Geophysical Research - Planets, 102(E2):4117–4129, February 1997. [10] Chris Leger, Ashitey Trebi-Ollenu, John Wright, Scott Maxwell, Bob Bonitz, Jeff Biesiadecki, Frank Hartman, 13

Figure 9. Plot of Opportunity’s complete drive history per sol through Sol 567; the most driving in one sol was 219 meters on Sol 410, the longest contiguous autonomous drive was 280 meters during sols 383–385. Note that the vertical scale here is more compressed than that in Figure 6. Red indicates blind driving, green indicates autonav (rows 5–8 in Table 2), blue indicates Visodom (rows 2, 4 in Table 2).

Figure 10. Plot of Opportunity’s complete tilt history through Sol 567. Report. Springer-Verlag, 1996.

Brian Cooper, Eric Baumgartner, and Mark Maimone. Mars Exploration Rover surface operations: Driving spirit at gusev crater. In IEEE Conference on Systems, Man and Cybernetics, The Big Island, Hawaii, USA, October 2005. [11] M. Maimone, L. Matthies, J. Osborn, E. Rollins, J. Teza, and S. Thayer. A photo-realistic 3-D mapping system for extreme nuclear environments: Chornobyl. In International Robotics and Systems Conference (IROS), pages 1521–1527, Victora B.C., Canada, October 1998. http://robotics.jpl.nasa.gov/people/mwm/pioneer/iros98/. [12] Mark Maimone, Jeffrey Biesiadecki, Edward Tunstel, Yang Cheng, and Chris Leger. Surface navigation and mobility intelligence on the Mars Exploration Rovers, chapter 3, pages 45–69. TSI Press, Albuquerque, NM, USA, 2006. http://www.intelligentspacerobotics.com/.

[15] L. Matthies, Y. Xiong, R. Hogg, D. Zhu, A. Rankin, B. Kennedy, M. Hebert, R. Maclachlan, C. Won, T. Frost, G. Sukhatme, M. McHenry, and S. Goldberg. A portable, autonomous urban reconnaissance robot. In Intelligent Autonomous Systems, Venice, Italy, July 2000. http://robotics.jpl.nasa.gov/ tasks/tmr/papers/UrbanRobotPaper0700.pdf. [16] L. H. Matthies. Stereo vision for planetary rovers: stochastic modeling to near real-time implementation. International Journal of Computer Vision, 8(1):71–91, July 1992. [17] A. Mishkin, J. Morrison, T. Nguyen, H. Stone, B. Cooper, and B. Wilcox. Experiences with operations and autonomy of the mars pathfinder microrover. In Proceedings of the 1998 IEEE Aerospace Conference, Snowmass at Aspen, Colorado, March 1998. http://robotics.jpl.nasa.gov/people/mishkin/papers/IEEE aerospace98.pdf.

[13] L. Matthies, E. Gat, R. Harrison, B. Wilcox, R. Volpe, and T. Litwin. Mars microrover navigation: Performance evaluation and enhancement. Autonomous Robots Journal, Special Issue on Autonomous Vehicle for Planetary Exploration, 2(4), 1995.

[18] A. Rankin, C. Bergh, S. Goldberg, and L. Matthies. Passive perception system for day/night autonomous offroad navigation. In SPIE UGV Symposium, Orlando, FL, April 2005.

[14] L. Matthies, A. Kelly, T. Litwin, and G. Tharp. Obstacle Detection for Unmanned Ground Vehicles: A Progress 14

[19] Glenn E. Reeves and Joseph F. Snyder. An overview of the Mars Exploration Rovers flight software. In IEEE Conference on Systems, Man and Cybernetics, The Big Island, Hawaii, USA, October 2005. [20] Reid Simmons, Lars Henriksen, Lonnie Chrisman, and Greg Whelan. Obstacle avoidance and safeguarding for a lunar rover. In AIAA Forum on Advanced Developments in Space robotics, Madison, WI, August 1996. http://www.cs.cmu.edu/˜reids/papers/AIAAobsAvoid.pdf. [21] Sanjiv Singh, Kurt Schwehr, Reid Simmons, Trey Smith, Anthony Stentz, Vandi Verma, and Alex Yahja. Recent progress in local and global traversability for planetary rovers. In International Conference on Robotics and Automation, 2000. http://www.frc.ri.cmu.edu/projects/mars/ publications/global local icra2000.ps.gz. [22] Richard Volpe. Navigation results from desert field tests of the Rocky 7 Mars rover prototype. International Journal of Robotics Research, 18(7):669–683, Special Issue on Field and Service Robots, July 1999. http://robotics.jpl.nasa.gov/people/volpe/papers/JnavMay.pdf. [23] Richard Volpe. Rover functional autonomy development for the Mars mobile science laboratory. In IEEE Aerospace Conference, Big Sky, Montana, March 2003. [24] David Wettergreen, Deepak Bapna, Mark Maimone, and Geb Thomas. Developing nomad for robotic exploration of the atacama desert. Robotics and Autonomous Systems, 26(2–3):127–148, February 1999. http://robotics.jpl.nasa.gov/people/mwm/papers/98ras.nomad.pdf. [25] Yalin Xiong and Larry Matthies. Error analysis of a real-time stereo system. In Computer Vision and Pattern Recognition, pages 1087–1093, 1997. http://www.cs.cmu.edu/˜yx/ papers/StereoError97.pdf.

15

The Mars Exploration Rover Surface Mobility Flight Software

Short Description

Description

Comments