The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Team IHMC's Lessons Learned from the DARPA Robotics Challenge Trials
Abstract
This article is a summary of the experiences of the Florida Institute for Human & Machine Cognition (IHMC) team during the DARPA Robotics Challenge (DRC) Trials. The primary goal of the DRC is to develop robots capable of assisting humans in responding to natural and manmade disasters. The robots are expected to use standard tools and equipment to accomplish the mission. The DRC Trials consisted of eight different challenges that tested robot mobility, manipulation, and control under degraded communications and time constraints. Team IHMC competed using the Atlas humanoid robot made by Boston Dynamics. We competed against 16 international teams and placed second in the competition. This article discusses the challenges we faced in transitioning from simulation to hardware. It also discusses the lessons learned both during the competition and in the months of preparation leading up to it. The lessons address the value of reliable hardware and solid software practices. They also cover effective approaches to bipedal walking and designing for human‐robot teamwork. Lastly, the lessons present a philosophical discussion about choices related to designing robotic systems.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
A compliant, underactuated hand for robust manipulation
Odhner, L. U., Jentoft, L. P., Claffee, M. R., Corson, N., Tenzer, Y., Ma, R. R., Buehler, M., Kohout, R., Howe, R. D., & Dollar, A. M. (2014) · The International Journal of Robotics Research · doi:10.1177/0278364913514466 · Cited by 598
Cited by
Optimization-based locomotion planning, estimation, and control design for the atlas humanoid robot
Kuindersma, S., Deits, R., Fallon, M., Valenzuela, A., Dai, H., Permenter, F., Koolen, T., Marion, P., & Tedrake, R. (2016) · Autonomous Robots · doi:10.1007/s10514-015-9479-3 · Cited by 835
Self-citationService robots in hotels: understanding the service quality perceptions of human-robot interaction
Choi, Y., Choi, M., Oh, M. (., & Kim, S. (. (2020) · Journal of Hospitality Marketing & Management · doi:10.1080/19368623.2020.1703871 · Cited by 522
Akata, Z., Balliet, D., de Rijke, M., Dignum, F., Dignum, V., Eiben, G., Fokkens, A., Grossi, D., Hindriks, K., Hoos, H., et al. (2020) · Computer · doi:10.1109/mc.2020.2996587 · Cited by 415
Interactive perception: Leveraging action in perception and perception in action
Bohg, J., Hausman, K., Sankaran, B., Brock, O., Kragic, D., Schaal, S., & Sukhatme, G. S. (2017) · IEEE Transactions on Robotics · doi:10.1109/tro.2017.2721939 · Cited by 227
Lessons from the Amazon Picking Challenge: Four Aspects of Building Robotic Systems
Eppner, C., Höfer, S., Jonschkowski, R., Martín-Martín, R., Sieverling, A., Wall, V., & Brock, O. (2017) · Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence · doi:10.24963/ijcai.2017/676 · Cited by 62
Metadata
- Authors
- Johnson, M., Shrewsbury, B., Bertrand, S., Wu, T., Duran, D., Floyd, M., Abeles, P., Stephen, D., Mertins, N., Lesman, A., Carff, J., Rifenburgh, W., Kaveti, P., Straatman, W., Smith, J., Griffioen, M., Layton, B., de Boer, T., Koolen, T., Neuhaus, P., & Pratt, J.
- Venue
- Journal of Field Robotics
- Publisher
- Wiley
- Published
- 2015-02-13
- Volume
- 32
- Issue
- 2
- Pages
- 192-208
- ISSN
- 1556-4959 (ISSN-L)
- 1556-4967
- OpenAlex
- W1820821744
- Cited by
- 250
- References
- 1
- FWCI
- 20.76
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Team IHMC's Lessons Learned from the DARPA Robotics Challenge Trials. https://app.cochat.ai/papers/10.1002/rob.21571
- The paper
- Johnson, M., Shrewsbury, B., Bertrand, S., Wu, T., Duran, D., Floyd, M., Abeles, P., Stephen, D., Mertins, N., Lesman, A., Carff, J., Rifenburgh, W., Kaveti, P., Straatman, W., Smith, J., Griffioen, M., Layton, B., de Boer, T., Koolen, T., . . . Pratt, J. (2015). Team IHMC's Lessons Learned from the DARPA Robotics Challenge Trials. Journal of Field Robotics. https://doi.org/10.1002/rob.21571
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
