Fast Motion Prediction for Collaborative Robotics
Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence. Pages 3988-3988.
Abstract
The efficient and safe performance of collaborative robots requires advancements in perception, control, design and algorithms, among other factors. With regard to algorithms, representing the structure of collaborative tasks and reasoning about progress toward task completion in an on-line fashion enables a robot to be a fluent and safe collaborator based on its ability to predict the next actions of a human agent. With this goal in mind, we focus on real-time target prediction of human reaching motion and present an algorithm based on time series classification. Results from on-line testing involving a tabletop task with a PR2 robot yielded 70% prediction accuracy with 400 msec of observed trajectory.
@inproceedings{ijcai2016p568,
title = {Fast Motion Prediction for Collaborative Robotics},
author = {Pérez-D'Arpino, Claudia and Shah, Julie A.},
booktitle = {Proceedings of the Twenty-Fifth International Joint Conference on
Artificial Intelligence, {IJCAI-16}},
publisher = {AAAI Press / International Joint Conferences on Artificial Intelligence},
editor = {Subbarao Kambhampati},
pages = {3988--3988},
year = {2016},
month = {7},
url = {https://ijcai.org/proceedings/2016/568},
}
TY - CPAPER TI - Fast Motion Prediction for Collaborative Robotics AU - Pérez-D'Arpino, Claudia AU - Shah, Julie A. T2 - Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, IJCAI-16 PB - AAAI Press / International Joint Conferences on Artificial Intelligence PY - 2016 SP - 3988 EP - 3988 UR - https://ijcai.org/proceedings/2016/568 ER -Copied
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