Title
Analysis of Affective Human Motion During Functional Task Performance: An Inverse Optimal Control Approach
Abstract
For robots that collaborate alongside and work with humans, there is great interest in improving robot communication abilities to achieve engaging and successful interactions. Successful task collaborations between humans often involve functional motions in which implicit communication signals, such as affect, are embedded. Thus in order to improve a robot's communication capabilities, it is necessary to identify the different motor control strategies that humans employ when generating such implicit signals. This paper details the adaptation of an Inverse Optimal Control (IOC) methodology for this purpose. We hypothesize that IOC allows for the identification of the motion strategies involved in the implicit communication of affective content during the performance of functional movement. To test our hypothesis, a motion capture dataset consisting of upper-body functional movements was collected and annotated by multiple observers through a perceptual user study. Among the different control strategies considered during our analysis, we found that center of mass movement, quantity of motion, Laban space effort and effort were the most relevant when distinguishing motions that convey different affective states.
Year
DOI
Venue
2019
10.1109/Humanoids43949.2019.9035007
2019 IEEE-RAS 19th International Conference on Humanoid Robots (Humanoids)
Keywords
DocType
ISSN
affective human motion,functional task performance,inverse optimal control approach,robot communication abilities,successful task collaborations,functional motions,implicit communication signals,motor control strategies,implicit signals,IOC,motion strategies,affective content,functional movement,motion capture dataset,upper-body functional movements,inverse optimal control methodology,affective states
Conference
2164-0572
ISBN
Citations 
PageRank 
978-1-5386-7631-8
0
0.34
References 
Authors
12
5
Name
Order
Citations
PageRank
Pamela Carreno-Medrano111.71
Tatsuki Harada200.34
Jonathan Feng-Shun Lin3274.07
Dana Kulic481069.21
Gentiane Venture520938.49