What happened at the DARPA robotics challenge finals

Christopher G. Atkeson, P. W.Babu Benzun, Nandan Banerjee, Dmitry Berenson, Christoper P. Bove, Xiongyi Cui, Mathew DeDonato, Ruixiang Du, Siyuan Feng, Perry Franklin, M. Gennert, Joshua P. Graff, Peng He, Aaron Jaeger, Joohyung Kim, Kevin Knoedler, Lening Li, Chenggang Liu, Xianchao Long, T. PadirFelipe Polido, G. G. Tighe, X. Xinjilefu

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

This paper summarizes observations and lessons learned by the WPI-CMU team and self-reports made by many of the DARPA Robotics Challenge teams on what happened at the DARPA Robotics Challenge Finals. Major conclusions are: (1) Reducing operator errors is the most cost effective way to improve robot performance. Methods include operator training and practice, and software safeguards to detect and prevent operator errors. (2) Super-human sensing is another way to greatly improve robot performance. To some extent this matches what happened in the DARPA autonomous driving challenges, in which improved sensing was the key to improved performance. (3) Paradigm shifts are needed in academic robotics, such as emphasizing designing robust behaviors, systems design including what seem like unimportant issues such as thermal management, and consistent real world results rather than videos of the rare successes.

Original languageEnglish (US)
Title of host publicationSpringer Tracts in Advanced Robotics
PublisherSpringer
Pages667-684
Number of pages18
DOIs
StatePublished - 2018
Externally publishedYes

Publication series

NameSpringer Tracts in Advanced Robotics
Volume121
ISSN (Print)1610-7438
ISSN (Electronic)1610-742X

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Artificial Intelligence

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