Into the Robotic Depths: Analysis and Insights from the DARPA Subterranean Challenge

Literature Cited

1. 1.

   Natl. Mine Health Saf. Acad 2013. Advanced mine rescue training: coal mines Instr. Guide 7, Natl. Mine Health Saf. Acad., Mine Saf. Health Adm., US Dep. Labor Beaver, WV:
2. 2.

   Fed. Emerg. Manag. Agency 2006. National Urban Search and Rescue (US&R) Response System: rescue field operations guide Doc. US&R-23-FG, Fed. Emerg. Manag. Agency Washington, DC:
3. 3.

   Mirza A 2018. Manual of U.S. Cave Rescue Techniques Huntsville, AL: Natl. Speleol. Soc., 3rd ed.., v. 2.1
4. 4.

   US Dep. Army 2019. Subterranean operations Army Tech. Publ. 3-21.51, US Dep. Army Washington, DC:
5. 5.

   Def. Adv. Proj. Res. Agency (DARPA) 2021. Competition rules: Final Event. Doc., Tactical Technol. Off., DARPA Arlington, VA: https://www.subtchallenge.com/resources/SubT_Challenge_Finals_Rules.pdf
6. 6.

   Def. Adv. Proj. Res. Agency (DARPA) 2021. Interface control document: Systems Competition Final Event. Doc., Tactical Technol. Off., DARPA Arlington, VA: https://www.subtchallenge.com/resources/SubT_Challenge_Finals_ICD.pdf
7. 7.

   Def. Adv. Proj. Res. Agency (DARPA), SubT Chall. Teams 2022. subt_resources. GitHub https://github.com/subtchallenge/subt_resources
   [Google Scholar]
8. 8.

   Tranzatto M, Miki T, Dharmadhikari M, Bernreiter L, Kulkarni M et al. 2022. CERBERUS in the DARPA Subterranean Challenge. Sci. Robot. 7:eabp9742
   [Google Scholar]
9. 9.

   Hudson N, Talbot F, Cox M, Williams J, Hines T et al. 2021. Heterogeneous ground and air platforms, homogeneous sensing: Team CSIRO Data61’s approach to the DARPA Subterranean Challenge. Field Robot. 2:595–636
   [Google Scholar]
10. 10.

    Ohradzansky MT, Rush ER, Riley DG, Mills AB, Ahmad S et al. 2021. Multi-agent autonomy: advancements and challenges in subterranean exploration. Field Robot. 2:1068–104
    [Google Scholar]
11. 11.

    Agha A, Otsu K, Morrell B, Fan DD, Thakker R et al. 2021. NeBula: TEAM CoSTAR's robotic autonomy solution that won phase II of DARPA Subterranean Challenge. Field Robot. 2:1432–506
    [Google Scholar]
12. 12.

    Rouček T, Pecka M, Čížek P, Petříček T, Bayer J et al. 2021. System for multi-robotic exploration of underground environments: CTU-CRAS-NORLAB in the DARPA Subterranean Challenge. Field Robot. 2:1779–818
    [Google Scholar]
13. 13.

    Miki T, Lee J, Hwangbo J, Wellhausen L, Koltun V, Hutter M. 2022. Learning robust perceptive locomotion for quadrupedal robots in the wild. Sci. Robot. 7:eabk2822
    [Google Scholar]
14. 14.

    Báča T, Petrlík M, Vrba M, Spurný V, Pěnička R et al. 2021. The MRS UAV system: pushing the frontiers of reproducible research, real-world deployment, and education with autonomous unmanned aerial vehicles. J. Intell. Robot. Syst. 102:26
    [Google Scholar]
15. 15.

    Bateman S, Harlow K, Heckman C. 2020. Better together: online probabilistic clique change detection in 3D landmark-based maps. 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)4878–85. Piscataway, NJ: IEEE
    [Google Scholar]
16. 16.

    Khattak S, Nguyen H, Mascarich F, Dang T, Alexis K 2020. Complementary multi-modal sensor fusion for resilient robot pose estimation in subterranean environments. 2020 International Conference on Unmanned Aircraft Systems (ICUAS)1024–29. Piscataway, NJ: IEEE
    [Google Scholar]
17. 17.

    Hines T, Stepanas K, Talbot F, Sa I, Lewis J et al. 2021. Virtual surfaces and attitude aware planning and behaviours for negative obstacle navigation. IEEE Robot. Autom. Lett. 6:4048–55
    [Google Scholar]
18. 18.

    Bouman A, Ginting M, Alatur N, Palieri M, Fan D et al. 2020. Autonomous Spot: long-range autonomous exploration of extreme environments with legged locomotion. 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)2518–25. Piscataway, NJ: IEEE
    [Google Scholar]