TY - GEN
T1 - A human factors analysis of proactive support in human-robot teaming
AU - Zhang, Yu
AU - Narayanan, Vignesh
AU - Chakraborti, Tathagata
AU - Kambhampati, Subbarao
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/12/11
Y1 - 2015/12/11
N2 - It has long been assumed that for effective human-robot teaming, it is desirable for assistive robots to infer the goals and intents of the humans, and take proactive actions to help them achieve their goals. However, there has not been any systematic evaluation of the accuracy of this claim. On the face of it, there are several ways a proactive robot assistant can in fact reduce the effectiveness of teaming. For example, it can increase the cognitive load of the human teammate by performing actions that are unanticipated by the human. In such cases, even though the teaming performance could be improved, it is unclear whether humans are willing to adapt to robot actions or are able to adapt in a timely manner. Furthermore, misinterpretations and delays in goal and intent recognition due to partial observations and limited communication can also reduce the performance. In this paper, our aim is to perform an analysis of human factors on the effectiveness of such proactive support in human-robot teaming. We perform our evaluation in a simulated Urban Search and Rescue (USAR) task, in which the efficacy of teaming is not only dependent on individual performance but also on teammates' interactions with each other. In this task, the human teammate is remotely controlling a robot while working with an intelligent robot teammate 'Mary'. Our main result shows that the subjects generally preferred Mary with the ability to provide proactive support (compared to Mary without this ability). Our results also show that human cognitive load was increased with a proactive assistant (albeit not significantly) even though the subjects appeared to interact with it less.
AB - It has long been assumed that for effective human-robot teaming, it is desirable for assistive robots to infer the goals and intents of the humans, and take proactive actions to help them achieve their goals. However, there has not been any systematic evaluation of the accuracy of this claim. On the face of it, there are several ways a proactive robot assistant can in fact reduce the effectiveness of teaming. For example, it can increase the cognitive load of the human teammate by performing actions that are unanticipated by the human. In such cases, even though the teaming performance could be improved, it is unclear whether humans are willing to adapt to robot actions or are able to adapt in a timely manner. Furthermore, misinterpretations and delays in goal and intent recognition due to partial observations and limited communication can also reduce the performance. In this paper, our aim is to perform an analysis of human factors on the effectiveness of such proactive support in human-robot teaming. We perform our evaluation in a simulated Urban Search and Rescue (USAR) task, in which the efficacy of teaming is not only dependent on individual performance but also on teammates' interactions with each other. In this task, the human teammate is remotely controlling a robot while working with an intelligent robot teammate 'Mary'. Our main result shows that the subjects generally preferred Mary with the ability to provide proactive support (compared to Mary without this ability). Our results also show that human cognitive load was increased with a proactive assistant (albeit not significantly) even though the subjects appeared to interact with it less.
KW - Cameras
KW - Human factors
KW - Intelligent robots
KW - Planning
KW - Robot vision systems
KW - Systematics
UR - http://www.scopus.com/inward/record.url?scp=84958180266&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84958180266&partnerID=8YFLogxK
U2 - 10.1109/IROS.2015.7353878
DO - 10.1109/IROS.2015.7353878
M3 - Conference contribution
AN - SCOPUS:84958180266
T3 - IEEE International Conference on Intelligent Robots and Systems
SP - 3586
EP - 3593
BT - IROS Hamburg 2015 - Conference Digest
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2015
Y2 - 28 September 2015 through 2 October 2015
ER -