2020 International Conference Mechatronic Systems and Materials (MSM) 2020
DOI: 10.1109/msm49833.2020.9202398
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Collaborative Robot System for Playing Chess

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Cited by 11 publications
(6 citation statements)
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“…The board is usually less problematic to be recognized since computer vision libraries, like the opensource OpenCV, provide many tested and robust algorithms based on model recognition suitable to fulfill this purpose. Examples are Harris corner detection [11,12], Canny edge detection, and Hough Line Transform [13,14]. These algorithms are suitable when the relative position between the robot and board can change since they find the board position fairly accurately and quickly.…”
Section: Related Workmentioning
confidence: 99%
See 1 more Smart Citation
“…The board is usually less problematic to be recognized since computer vision libraries, like the opensource OpenCV, provide many tested and robust algorithms based on model recognition suitable to fulfill this purpose. Examples are Harris corner detection [11,12], Canny edge detection, and Hough Line Transform [13,14]. These algorithms are suitable when the relative position between the robot and board can change since they find the board position fairly accurately and quickly.…”
Section: Related Workmentioning
confidence: 99%
“…In this manner, the gripper can correctly reach and grasp the pieces. As robotic agents, robotic arms are mainly used [12,14,18] thanks to their dexterity and manipulation capability. Cartesian mechanisms are also used [19,26] due to their easy control, but their structure is often large and bulky.…”
Section: Related Workmentioning
confidence: 99%
“…It only provides a very high level information on the performance of the system. For example, [17], a collaborative robot capable of playing chess with a human or with another cobot is presented and the main requirement of this system is accuracy in the sense of "success of the task". In order for a cobot to be able to perform such a difficult task, the author divided it into three subtasks: the vision algorithm, the decision making algorithm, and the manipulator control system.…”
Section: A Accuracymentioning
confidence: 99%
“…During recognitions on chess pieces, most systems combined computer vision with robotic development for application in a real usage scenario [11][12][13][14]. They can trace each move in a chess game with a realtime speed by finding differences between two neighboring movements [15]. However, most tracing systems must run under the premise that the initial layout of the chess map is known, which added redundant manual interventions.…”
Section: Introductionmentioning
confidence: 99%