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Main Authors: Sucker, Sascha, Neubauer, Michael, Henrich, Dominik
Format: Preprint
Published: 2024
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Online Access:https://arxiv.org/abs/2411.09436
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author Sucker, Sascha
Neubauer, Michael
Henrich, Dominik
author_facet Sucker, Sascha
Neubauer, Michael
Henrich, Dominik
contents Natural language allows robot programming to be accessible to everyone. However, the inherent fuzziness in natural language poses challenges for inflexible, traditional robot systems. We focus on instructions with fuzzy time requirements (e.g., "start in a few minutes"). Building on previous robotics research, we introduce fuzzy skills. These define an execution by the robot with so-called satisfaction functions representing vague execution time requirements. Such functions express a user's satisfaction over potential starting times for skill execution. When the robot handles multiple fuzzy skills, the satisfaction function provides a temporal tolerance window for execution, thus, enabling optimal scheduling based on satisfaction. We generalized such functions based on individual user expectations with a user study. The participants rated their satisfaction with an instruction's execution at various times. Our investigations reveal that trapezoidal functions best approximate the users' satisfaction. Additionally, the results suggest that users are more lenient if the execution is specified further into the future.
format Preprint
id arxiv_https___arxiv_org_abs_2411_09436
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Robot Tasks with Fuzzy Time Requirements from Natural Language Instructions
Sucker, Sascha
Neubauer, Michael
Henrich, Dominik
Robotics
Computation and Language
Human-Computer Interaction
Natural language allows robot programming to be accessible to everyone. However, the inherent fuzziness in natural language poses challenges for inflexible, traditional robot systems. We focus on instructions with fuzzy time requirements (e.g., "start in a few minutes"). Building on previous robotics research, we introduce fuzzy skills. These define an execution by the robot with so-called satisfaction functions representing vague execution time requirements. Such functions express a user's satisfaction over potential starting times for skill execution. When the robot handles multiple fuzzy skills, the satisfaction function provides a temporal tolerance window for execution, thus, enabling optimal scheduling based on satisfaction. We generalized such functions based on individual user expectations with a user study. The participants rated their satisfaction with an instruction's execution at various times. Our investigations reveal that trapezoidal functions best approximate the users' satisfaction. Additionally, the results suggest that users are more lenient if the execution is specified further into the future.
title Robot Tasks with Fuzzy Time Requirements from Natural Language Instructions
topic Robotics
Computation and Language
Human-Computer Interaction
url https://arxiv.org/abs/2411.09436