Robotic systems are traditionally programmed through offline coding interfaces for manipulation or navigation tasks. These programming methods are usually time-consuming and cost a lot of human efforts. To address this issue, we developed a human-friendly method to program robots manipulation tasks through human-robot interaction by natural language. The new programming method consists of three processes: human teaching, robot learning and robot execution. Through them, the humans are able to use natural language to on site program robot manipulation tasks which can involve operations of both single and groups of objects.
Publications
1. Y. Cheng, J. Bao, Y. Jia, Z. Deng, Z. Sun, S. Bi, C. Li and N. Xi. Modeling Robotic Operations Controlled by Natural Language. Control Theory and Technology, 2017, 5(4): 258-266.
2. Y. Cheng, J. Bao, Y. Jia, Z. Deng, Z. Sun, S. Bi, C. Li and N. Xi. Modeling Natural Language Controlled Robotic Operations. IEEE Conference on Cyber Technology in Automation, Control, and Intelligent Systems (CYBER), 2017.
3. Y. Jia, L. She, Y. Cheng, J. Bao, J. Chai and N. Xi. Program Robots Manufacturing Tasks by Natural Language Instructions. IEEE/RAS International Conference on Automation Science and Engineering (CASE), 2016.
4. Y. Cheng, J. Bao, Y. Jia, Z. Deng, L. Dong, and N. Xi. Analytic Approach for Natural Language based Supervisory Control of Robotic Manipulations. IEEE International Conference on Robotics and Biomimetics (ROBIO), 2016. (Best Student Paper Award)
5. L. She, Y. Cheng, J. Chai, Y. Jia, S. Yang and N. Xi. Teaching Robots New Actions through Natural Language Instructions. IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN), 2014.
6. L. She, S. yang, Y. Cheng, Y. Jia, J. Chai and N. Xi. Back to the Blocks World: Learning New Actions through Situated Human-Robot Dialogue. 15th Annual SIGdial Meeting on Discourse and Dialogue (SIGDIAL), 2014, pp. 89-97.
7. Y. Jia, N. Xi, J. Chai, Y. Cheng, R. Fang and L. She, Perceptive Feedback for Natural Language Control of Robotic Operators. IEEE Conference on Robotics and Automation (ICRA), 2014, pp. 6673-6678.
Video Demonstrations