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Novel end-user programming (EUP) tools enable on-the-fly (i.e., spontaneous, easy, and rapid) creation of interactions with robotic systems. These tools are expected to empower users in determining system behavior, although very little is understood about how end users perceive, experience, and use these systems. In this paper, we seek to address this gap by investigating end-user experience with on-the-fly robot EUP. We trained 21 end users to use an existing on-the-fly EUP tool, asked them to create robot interactions for four scenarios, and assessed their overall experience. Our findings provide insight into how these systems should be designed to better support end-user experience with on-the-fly EUP, focusing on user interaction with an automatic program synthesizer that resolves imprecise user input, the use of multimodal inputs to express user intent, and the general process of programming a robot.
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Transforming Robot Programs Based on Social Context
Social robots have varied effectiveness when interacting with humans in different interaction contexts. A robot programmed to escort individuals to a different location, for instance, may behave more appropriately in a crowded airport than a quiet library, or vice versa. To address these issues, we exploit ideas from program synthesis and propose an approach to transforming the structure of hand-crafted interaction programs that uses user-scored execution traces as input, in which end users score their paths through the interaction based on their experience. Additionally, our approach guarantees that transformations to a program will not violate task and social expectations that must be maintained across contexts. We evaluated our approach by adapting a robot program to both real-world and simulated contexts and found evidence that making informed edits to the robot's program improves user experience.
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- PAR ID:
- 10198128
- Date Published:
- Journal Name:
- CHI '20: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems
- Page Range / eLocation ID:
- 1 to 12
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1145/3313831.3376355
