Limits...
Analyzing the effects of human-aware motion planning on close-proximity human-robot collaboration.

Lasota PA, Shah JA - Hum Factors (2015)

Bottom Line: The objective of this work was to examine human response to motion-level robot adaptation to determine its effect on team fluency, human satisfaction, and perceived safety and comfort.People respond well to motion-level robot adaptation, and significant benefits can be achieved from its use in terms of both human-robot team fluency and human worker satisfaction.Our conclusion supports the development of technologies that could be used to implement human-aware motion planning in collaborative robots and the use of this technique for close-proximity human-robot collaboration.

View Article: PubMed Central - PubMed

ABSTRACT

Objective: The objective of this work was to examine human response to motion-level robot adaptation to determine its effect on team fluency, human satisfaction, and perceived safety and comfort.

Background: The evaluation of human response to adaptive robotic assistants has been limited, particularly in the realm of motion-level adaptation. The lack of true human-in-the-loop evaluation has made it impossible to determine whether such adaptation would lead to efficient and satisfying human-robot interaction.

Method: We conducted an experiment in which participants worked with a robot to perform a collaborative task. Participants worked with an adaptive robot incorporating human-aware motion planning and with a baseline robot using shortest-path motions. Team fluency was evaluated through a set of quantitative metrics, and human satisfaction and perceived safety and comfort were evaluated through questionnaires.

Results: When working with the adaptive robot, participants completed the task 5.57% faster, with 19.9% more concurrent motion, 2.96% less human idle time, 17.3% less robot idle time, and a 15.1% greater separation distance. Questionnaire responses indicated that participants felt safer and more comfortable when working with an adaptive robot and were more satisfied with it as a teammate than with the standard robot.

Conclusion: People respond well to motion-level robot adaptation, and significant benefits can be achieved from its use in terms of both human-robot team fluency and human worker satisfaction.

Application: Our conclusion supports the development of technologies that could be used to implement human-aware motion planning in collaborative robots and the use of this technique for close-proximity human-robot collaboration.

Show MeSH

Related in: MedlinePlus

Mean values, with error bars indicating standard error of the mean (SEM), of (a) percentage of concurrent motion, (b) robot idle time, and (c) average separation distance between the human and robot for groups of participants working with the standard and human-aware robots prior to exposure to the second robot type.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2 - License 3
getmorefigures.php?uid=PMC4359211&req=5

fig5-0018720814565188: Mean values, with error bars indicating standard error of the mean (SEM), of (a) percentage of concurrent motion, (b) robot idle time, and (c) average separation distance between the human and robot for groups of participants working with the standard and human-aware robots prior to exposure to the second robot type.

Mentions: In regard to data collected up to the administration of the first survey (see Figure 3), each participant was exposed only to a single robot type. Consequently, we can treat the team fluency metric data from the two groups of participants, those who worked with a standard robot and those who worked with a human-aware robot, as independent. Significant differences between these populations emerged for three of the five team fluency metrics considered when analyzed with one-way ANOVAs. Once again, the normality of the data was assessed with the Shapiro-Wilk test, and none of the distributions was significantly different from normal, minimum W(11) = 0.862, p = .061. The group of participants that worked with the human-aware robot completed the task with 15.0% more concurrent motion, F(1, 18) = 5.68, p = .028; 14.6% less robot idle time, F(1, 18) = 6.41, p = .021; and a 17.3% larger separation distance, F(1, 18) =19.83, p < .001. The mean values of both groups of participants for each of these metrics along with error bars depicting standard error of the mean are shown in Figure 5.


Analyzing the effects of human-aware motion planning on close-proximity human-robot collaboration.

Lasota PA, Shah JA - Hum Factors (2015)

Mean values, with error bars indicating standard error of the mean (SEM), of (a) percentage of concurrent motion, (b) robot idle time, and (c) average separation distance between the human and robot for groups of participants working with the standard and human-aware robots prior to exposure to the second robot type.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2 - License 3
Show All Figures
getmorefigures.php?uid=PMC4359211&req=5

fig5-0018720814565188: Mean values, with error bars indicating standard error of the mean (SEM), of (a) percentage of concurrent motion, (b) robot idle time, and (c) average separation distance between the human and robot for groups of participants working with the standard and human-aware robots prior to exposure to the second robot type.
Mentions: In regard to data collected up to the administration of the first survey (see Figure 3), each participant was exposed only to a single robot type. Consequently, we can treat the team fluency metric data from the two groups of participants, those who worked with a standard robot and those who worked with a human-aware robot, as independent. Significant differences between these populations emerged for three of the five team fluency metrics considered when analyzed with one-way ANOVAs. Once again, the normality of the data was assessed with the Shapiro-Wilk test, and none of the distributions was significantly different from normal, minimum W(11) = 0.862, p = .061. The group of participants that worked with the human-aware robot completed the task with 15.0% more concurrent motion, F(1, 18) = 5.68, p = .028; 14.6% less robot idle time, F(1, 18) = 6.41, p = .021; and a 17.3% larger separation distance, F(1, 18) =19.83, p < .001. The mean values of both groups of participants for each of these metrics along with error bars depicting standard error of the mean are shown in Figure 5.

Bottom Line: The objective of this work was to examine human response to motion-level robot adaptation to determine its effect on team fluency, human satisfaction, and perceived safety and comfort.People respond well to motion-level robot adaptation, and significant benefits can be achieved from its use in terms of both human-robot team fluency and human worker satisfaction.Our conclusion supports the development of technologies that could be used to implement human-aware motion planning in collaborative robots and the use of this technique for close-proximity human-robot collaboration.

View Article: PubMed Central - PubMed

ABSTRACT

Objective: The objective of this work was to examine human response to motion-level robot adaptation to determine its effect on team fluency, human satisfaction, and perceived safety and comfort.

Background: The evaluation of human response to adaptive robotic assistants has been limited, particularly in the realm of motion-level adaptation. The lack of true human-in-the-loop evaluation has made it impossible to determine whether such adaptation would lead to efficient and satisfying human-robot interaction.

Method: We conducted an experiment in which participants worked with a robot to perform a collaborative task. Participants worked with an adaptive robot incorporating human-aware motion planning and with a baseline robot using shortest-path motions. Team fluency was evaluated through a set of quantitative metrics, and human satisfaction and perceived safety and comfort were evaluated through questionnaires.

Results: When working with the adaptive robot, participants completed the task 5.57% faster, with 19.9% more concurrent motion, 2.96% less human idle time, 17.3% less robot idle time, and a 15.1% greater separation distance. Questionnaire responses indicated that participants felt safer and more comfortable when working with an adaptive robot and were more satisfied with it as a teammate than with the standard robot.

Conclusion: People respond well to motion-level robot adaptation, and significant benefits can be achieved from its use in terms of both human-robot team fluency and human worker satisfaction.

Application: Our conclusion supports the development of technologies that could be used to implement human-aware motion planning in collaborative robots and the use of this technique for close-proximity human-robot collaboration.

Show MeSH
Related in: MedlinePlus