In this paper, we analyze and report on observable trends in human-human dyads performing collaborative manipulation (co-manipulation) tasks with an extended object (object with significant length). We present a detailed analysis relating trends in interaction forces and torques with other metrics and propose that these trends could provide a way of improving communication and efficiency for human-robot dyads. We find that the motion of the co-manipulated object has a measurable oscillatory component. We confirm that haptic feedback alone represents a sufficient communication channel for co-manipulation tasks, however we find that the loss of visual and auditory channels has a significant effect on interaction torque and velocity. The main objective of this paper is to lay the essential groundwork in defining principles of co-manipulation between human dyads. We propose that these principles could enable effective and intuitive human-robot collaborative manipulation in future co-manipulation research.
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Theory of Mind Assessment with Human-Human and Human-Robot Interactions
Human-robot interaction has played an increasingly significant role in more recent research involving the Theory of Mind (ToM). As the use of robot facilitators increases, questions arise regarding the implications of their involvement in a research setting. This work addresses the effects of a humanoid robot facilitator in a ToM assessment. This paper analyzes subjects’ performances on tasks meant to test ToM as those tasks are delivered by human or robot facilitators. Various modalities of data were collected: performance on ToM tasks, subjects’ perceptions of the robot, results from a ToM survey, and response duration. This paper highlights the effects of human-robot interactions in ToM assessments, which ultimately leads to a discussion on the effectiveness of using robot facilitators in future human-subject research.
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- Award ID(s):
- 1851591
- NSF-PAR ID:
- 10401579
- Date Published:
- Journal Name:
- Human-Computer Interaction. Technological Innovation. HCII 2022. Lecture Notes in Computer Science
- Volume:
- 13303
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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