Human-Aware Robot Task Planning with Robot Execution Time Estimation

被引:1
|
作者
Braun, Mitchell [1 ]
Cheng, Yujiao [1 ]
Tomizuka, Masayoshi [1 ]
机构
[1] Univ Calif Berkeley, Berkeley, CA 94720 USA
来源
IFAC PAPERSONLINE | 2022年 / 55卷 / 41期
关键词
Flexible manufacturing; assistive robotics; shared control; task planning;
D O I
10.1016/j.ifacol.2023.01.123
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
When robots work with humans for a collaborative task, they need to plan their actions while taking humans actions into account. The state-of-the-art optimization-based human-aware task planner plans robot actions by prioritizing the actions that are parallel to the human's actions. However, the limitation of this approach is that the robot execution time for each action, which is an important parameter for the optimization problem, is fixed. In this paper, we investigate how online robot execution time estimation can increase the time efficiency of such a human-aware task planner. We propose a direct time estimation method and an analytical time estimation method. An integrated task and trajectory planning framework is also presented. Experiments show that online robot execution time estimation increases the time efficiency of the collaborative task. Moreover, the results of the direct time estimation method are more accurate than those of the analytical method. Copyright (c) 2022 The Authors. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/)
引用
收藏
页码:181 / 186
页数:6
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