The Department of Defense’s strategic plan calls for the Joint Force to conduct humanitarian, disaster relief, and related operations. Some disasters, due to grave risks to the health and wellbeing of rescue and aid workers, prove too great in scale or scope for timely and effective human response. The DARPA Robotics Challenge (DRC) seeks to address this problem by promoting innovation in human-supervised robotic technology for disaster-response operations. The primary technical goal of the DRC is to develop human-supervised ground robots capable of executing complex tasks in dangerous, degraded, human-engineered environments. Competitors in the DRC are developing robots that can utilize standard tools and equipment commonly available in human environments, ranging from hand tools to vehicles. To achieve its goal, the DRC is advancing the state of the art of supervised autonomy, mounted and dismounted mobility, and platform dexterity, strength, and endurance. Improvements in supervised autonomy, in particular, aim to enable better control of robots by non-expert supervisors and allow effective operation despite degraded communications (low bandwidth, high latency, intermittent connection). The DRC program website provides program highlights, including the DRC Trials held in December 2013 and the DRC Finals in June 2015.
Li, L., Long, X., & Gennert, M. A. (2016). Birrtopt: A combined sampling and optimizing motion planner for humanoid robots. 2016 IEEE-RAS 16th International Conference on Humanoid Robots (Humanoids), 469–476.
Atkeson, C. G., Babu, B. P. W., Banerjee, N., Berenson, D., Bove, C. P., Cui, X., DeDonato, M., Du, R., Feng, S., Franklin, P., & others. (2015). No falls, no resets: Reliable humanoid behavior in the DARPA robotics challenge. 2015 IEEE-RAS 15th International Conference on Humanoid Robots (Humanoids), 623–630.
DeDonato, M., Polido, F., Knoedler, K., Babu, B. P. W., Banerjee, N., Bove, C. P., Cui, X., Du, R., Franklin, P., Graff, J. P., & others. (2017). Team WPI-CMU: achieving reliable humanoid behavior in the DARPA robotics challenge. Journal of Field Robotics, 34(2), 381–399.
Atkeson, C. G., Benzun, P. W. B., Banerjee, N., Berenson, D., Bove, C. P., Cui, X., DeDonato, M., Du, R., Feng, S., Franklin, P., & others. (2018). What happened at the DARPA robotics challenge finals. In The DARPA robotics challenge finals: Humanoid robots to the rescue (pp. 667–684). Springer.
Atkeson, C. G., Benzun, P. W. B., Banerjee, N., Berenson, D., Bove, C. P., Cui, X., DeDonato, M., Du, R., Feng, S., Franklin, P., & others. (2018). Achieving reliable humanoid robot operations in the DARPA robotics challenge: team WPI-CMU’s approach. In The DARPA Robotics Challenge Finals: Humanoid Robots To The Rescue (pp. 271–307). Springer.
Li, L., Long, X., & Gennert, M. A. (2016). Birrtopt: A combined sampling and optimizing motion planner for humanoid robots. 2016 IEEE-RAS 16th International Conference on Humanoid Robots (Humanoids), 469–476.