[1]王玉卓,闵华松.基于毛笔建模的机器人书法系统[J].智能系统学报,2021,16(4):707-716.[doi:10.11992/tis.202006033]
WANG Yuzhuo,MIN Huasong.Robot calligraphy system based on brush modeling[J].CAAI Transactions on Intelligent Systems,2021,16(4):707-716.[doi:10.11992/tis.202006033]
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WANG Yuzhuo,MIN Huasong.Robot calligraphy system based on brush modeling[J].CAAI Transactions on Intelligent Systems,2021,16(4):707-716.[doi:10.11992/tis.202006033]
基于毛笔建模的机器人书法系统
《智能系统学报》[ISSN 1673-4785/CN 23-1538/TP] 卷:
16
期数:
2021年第4期
页码:
707-716
栏目:
学术论文—智能系统
出版日期:
2021-07-05
- Title:
- Robot calligraphy system based on brush modeling
- Keywords:
- robot calligraphy; brush modeling; genetic algorithm; writing rules; path planning; posture change; calligraphy evaluation; stroke characteristics
- 分类号:
- TP242.6
- 摘要:
- 针对机器人书法系统存在仅考虑毛笔笔直状态下机器人书写的问题，提出了一种新的机器人书法系统，可使机器人能够在倾斜状态下书写汉字。该系统首先分析毛笔足迹，建立一种适合用于机器人毛笔书写的基于线性回归算法的笔触模型；然后使用遗传算法从笔画图像获得轨迹信息，加入了起笔、行笔、收笔规则，生成虚拟笔画图像；最后采用B样条算法实现机器人路径规划，坐标变换完成姿态计算，从而进行实际书写。机器人书法系统提取了3种笔画特征作为评价指标，实验结果表明：机器人毛笔书法系统可以得到较好的书写效果。
- Abstract:
- A novel robot calligraphy system is proposed to enable robots to write Chinese characters by using a brush in a slanted position, with the purpose of solving the problem of the existing robot calligraphy system taking only the straight state of the brush into consideration. First, writing marks are analyzed in this proposed system, and an appropriate stroke model is established based on the linear regression algorithm. Then, the trajectory information is obtained from the stroke image by using genetic algorithms, which are added with the rules of starting, running, and closing for virtual stroke images. Lastly, path planning for robots is realized by using a B-spline algorithm, and posture calculation is fulfilled through coordinate transformation, thereby achieving actual writing. In the experiments, three stroke characteristics are extracted as evaluation indicators. Experimental results show that the robot brush calligraphy system can achieve a better writing effect.
- 参考文献/References:
-
[1] GAN Lin, FANG Wubing, CHAO Fei, et al. Towards a robotic Chinese calligraphy writing framework[C]//Proceedings of 2018 IEEE International Conference on Robotics and Biomimetics. Kuala Lumpur, Malaysia, 2018: 493-498.
[2] GAO Xingen, ZHOU Changle, CHAO Fei, et al. A data-driven robotic Chinese calligraphy system using convolutional auto-encoder and differential evolution[J]. Knowledge-based systems, 2019, 182: 104802.
[3] LI Quanfeng, FEI Chao, GAO Xingen, et al. A robotic Chinese stroke generation model based on competitive swarm optimizer[C]//Proceedings of Contributions Presented at the 19th UK Workshop on Computational Intelligence. Portsmouth, UK, 2019: 92-103.
[4] WU Ruiqi, FANG Wubing, CHAO Fei, et al. Towards deep reinforcement learning based Chinese calligraphy robot[C]//Proceedings of 2018 IEEE International Conference on Robotics and Biomimetics. Kuala Lumpur, Malaysia, 2018: 507-512.
[5] LI Jie, MIN Huasong, ZHOU Haotian, et al. Robot brush-writing system of Chinese calligraphy characters[C]//Proceedings of the 12th International Conference on Intelligent Robotics and Applications. Shenyang, China, 2019: 86-96.
[6] MUELLER S, HUEBEL N, WAIBEL M, et al. Robotic calligraphy—learning how to write single strokes of Chinese and Japanese characters[C]//Proceedings of 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems. Tokyo, Japan, 2013: 1734-1739.
[7] XU Pengfei, WANG Lei, GUAN Ziyu, et al. Evaluating brush movements for Chinese calligraphy: a computer vision based approach[C]//Proceedings of the 27th International Joint Conference on Artificial Intelligence. Stockholm, Sweden, 2018: 1050-1056.
[8] WANG Mengdi, FU Qian, WANG Xingce, et al. Evaluation of Chinese calligraphy by using DBSC vectorization and ICP algorithm[J]. Mathematical problems in engineering, 2016, 2016: 4845092.
[9] ZHOU Dajun, GE Jiamin, WU Ruiqi, et al. A computational evaluation system of Chinese calligraphy via extended possibility-probability distribution method[C]//Proceedings of the 2017 13th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery. Guilin, China, 2017: 884-889.
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MI Xiaofeng, TANG Min, LIN Jianzhen, et al. An experience based virtual brush model[J]. Journal of computer research and development, 2003, 40(8): 1244-1251
[11] 张俊松, 张悠苗, 周昌乐. 书法临摹过程的交互式动画建模方法[J]. 计算机辅助设计与图形学学报, 2014, 26(6): 963-972
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[13] 闵华松. AUBOi5运动学仿真[EB/OL]. (2018-12-02)[2020-06-20] https://github.com/mhuasong/AUBO-Robot-on-ROS/blob/master/ch4_2_v1.pdf
MIN Huasong. AUBO i5 Kinematics Simulation[EB/OL]. (2018-12-02)[2020-06-20] https://github.com/mhuasong/AUBO-Robot-on-ROS/blob/master/ch4_2_v1.pdf
备注/Memo
收稿日期:2020-06-20。
基金项目:国家自然科学基金项目(61673304)；国家重点研发计划项目(2017YFB1300400)；湖北省科技创新专项重大项目(2019AAA071)；武汉市应用基础前沿项目(2018010401011275)
作者简介:王玉卓，硕士研究生，主要研究方向为智能机器人;闵华松，教授，博士生导师，中国人工智能学会认知系统与信息处理专业委员会常务委员，中国电子学会嵌入式系统与机器人分会委员，中国机械工程学会机器人分会委员。主要研究方向为嵌入式系统与智能机器人
通讯作者:闵华松.E-mail:mhuasong@wust.edu.cn
更新日期/Last Update:
1900-01-01