Dynamic Nonprehensile Manipulation of a Moving Object Using a Batting Primitive

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To achieve human-level object manipulation capability, a robot must be able to handle objects not only with prehensile manipulation, such as pick-and-place, but also with nonprehensile manipulation. To study nonprehensile manipulation, we studied robotic batting, a primitive form of nonprehensile manipulation. Batting is a challenging research area because it requires sophisticated and fast manipulation of moving objects and requires considerable improvement. In this paper, we designed a batting system for dynamic manipulation of a moving ball and proposed several algorithms to improve the task performance of batting. To improve the recognition accuracy of the ball, we proposed a circle-fitting method that complements color segmentation. This method enabled robust ball recognition against illumination. To accurately estimate the trajectory of the recognized ball, weighted least-squares regression considering the accuracy according to the distance of a stereo vision sensor was used for trajectory estimation, which enabled more accurate and faster trajectory estimation of the ball. Further, we analyzed the factors influencing the success rate of ball direction control and applied a constant posture control method to improve the success rate. Through the proposed methods, the ball direction control performance is improved.
Publisher
MDPI
Issue Date
2021-05
Language
English
Article Type
Article
Citation

APPLIED SCIENCES-BASEL, v.11, no.9

ISSN
2076-3417
DOI
10.3390/app11093920
URI
http://hdl.handle.net/10203/285591
Appears in Collection
ME-Journal Papers(저널논문)
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