degrees in CSE from Madras University, the Ph.D. Vijayakumar received the Diploma degree (Hons.) in computer technology from the State Board of Tamil Nadu, the B.E.
His philosophical works lie in ancient oriental thoughts of Chinese, such as ZEN, TAO, YI etc., viewed from science. And beyond AI project, he also carries out research on a host of other topics including computational brain modeling, computational modeling of analogy and metaphor and creativity, computational musicology and information processing of data regarding traditional Chinese medicine. His scientific contribution to the AI has more to do with machine consciousness and the logic of mental self-reflection. His research interests lie in the areas of artificial intelligence. He is also an affiliated professor of linguistics and applied linguistics in the Humanity College at the Zhejiang University, and an affiliated professor of the Philosophy Department at the Xiamen University. Currently, he is a professor of the Department of Artificial Intelligence at the Xiamen University, the director of Fujian Provincial Key Laboratory of Brain-like Intelligent Systems, and the director of the Laboratory of Art, Mind and Computation. The experiments confirm the effectiveness of the proposed system in learning writing a certain style of characters based on a small style dataset, as evidenced by the high similarity between the robotic writing results and the handwritten ones according to the Fréchet Inception Distance.Ĭhangle Zhou received his Ph.D. From this, the robot can apply the learned writing style to any Chinese character from a given database, by dissembling the character and then generating the stroke trajectories based on the learned writing style.
This is achieved by firstly disassembling each given Chinese character into individual strokes using the proposed character disassemble method then, the writing style of the dissembled strokes is learned by a stroke generation module, which is built upon a generative adversarial learning model. Thanks to these mechanisms, the robot is able to effectively learn to write any Chinese characters in a style that is sampled by a small amount of handwritten Chinese characters with a certain target writing style. This paper presents an autonomous robotic writing system for Chinese calligraphy empowered by the proposed automatic stroke matching and generation mechanisms. Robotic calligraphy is such an attempt, and the current research focuses on the control algorithms of the robotic arms, which usually suffers from significant human inputs and limited writing styles. Intelligent robots, as an important type of Cyber–Physical systems, have promising potential to take the central stage in the development of the next-generation of efficient smart systems.