TY - GEN
T1 - Co-diagnosing configuration failures in co-robotic systems
AU - Taylor, Adam
AU - Elbaum, Sebastian
AU - Detweiler, Carrick
N1 - Funding Information:
This work was supported in part by NSF-1218265 and NRI-USDA-2013-67021-20947. We thank John-Paul Ore for his feedback on the manuscript.
Publisher Copyright:
© 2016 IEEE.
PY - 2016/11/28
Y1 - 2016/11/28
N2 - Robotic systems often have complex configuration spaces that, when poorly set, can cause failures. In this work we take advantage of the close synergy between user and robot in co-robotic systems to better diagnose and overcome configuration failures. We leverage users' understanding of the system to mark failures they observe while the system is in operation. A marked failure indicates that the robot either "did not do something when it should have" or "did something when it should not have". The failure marking is coupled with an automated analysis approach that identifies code predicates involving configuration parameters that may be relevant to each failure type, ranks the parameters according to their potential to be associated with the failure, and suggests adjustments based on the run-time outcome of those predicates.We present the approach, its implementation, and a preliminary study on a configurable unmanned air system. The results show how the approach can successfully help diagnose and adjust faulty configuration parameters in co-robotic systems.
AB - Robotic systems often have complex configuration spaces that, when poorly set, can cause failures. In this work we take advantage of the close synergy between user and robot in co-robotic systems to better diagnose and overcome configuration failures. We leverage users' understanding of the system to mark failures they observe while the system is in operation. A marked failure indicates that the robot either "did not do something when it should have" or "did something when it should not have". The failure marking is coupled with an automated analysis approach that identifies code predicates involving configuration parameters that may be relevant to each failure type, ranks the parameters according to their potential to be associated with the failure, and suggests adjustments based on the run-time outcome of those predicates.We present the approach, its implementation, and a preliminary study on a configurable unmanned air system. The results show how the approach can successfully help diagnose and adjust faulty configuration parameters in co-robotic systems.
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U2 - 10.1109/IROS.2016.7759454
DO - 10.1109/IROS.2016.7759454
M3 - Conference contribution
AN - SCOPUS:85006511863
T3 - IEEE International Conference on Intelligent Robots and Systems
SP - 2934
EP - 2939
BT - IROS 2016 - 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2016
Y2 - 9 October 2016 through 14 October 2016
ER -