The article presents multi-pattern formation exchange of mobile robots according to the image signals, programs motion paths using A＊ searching algorithm, and avoids the collision points of motion paths. The system c...The article presents multi-pattern formation exchange of mobile robots according to the image signals, programs motion paths using A＊ searching algorithm, and avoids the collision points of motion paths. The system contains an image system, a grid based motion platform, some wireless Radio Frequency （RF） modules and five mobile robots. We use image recognition algorithm to classify variety pattern formation according to variety Quick Response （QR） code symbols on the user interface of the supervised computer. The supervised computer controls five mobile robots to execute formation exchange and presents the movement scenario on the grid based motion platform. We have been developed some pattern formations according to game applications, such as long snake pattern formation, phalanx pattern formation, crane wing pattern formation, sword pattern formation, cone pattern formation, sward pattern tbrmation, T pattern formation, rectangle pattern formation and so on. We develop the user interface of the multi-robot system to program motion paths for variety pattern formation exchange according to the minimum displacement. In the experimental results, the supervised computer recognizes the various QR-code symbols using image system and decides which pattern formation to be selected on real-time. Mobile robots can receive the pattern formation command from the supervised computer, present the movement scenario from the original pattern formation to the assigned pattern formation on the motion platform, and avoid other mobile robots on real-time.展开更多
文摘The article presents multi-pattern formation exchange of mobile robots according to the image signals, programs motion paths using A＊ searching algorithm, and avoids the collision points of motion paths. The system contains an image system, a grid based motion platform, some wireless Radio Frequency （RF） modules and five mobile robots. We use image recognition algorithm to classify variety pattern formation according to variety Quick Response （QR） code symbols on the user interface of the supervised computer. The supervised computer controls five mobile robots to execute formation exchange and presents the movement scenario on the grid based motion platform. We have been developed some pattern formations according to game applications, such as long snake pattern formation, phalanx pattern formation, crane wing pattern formation, sword pattern formation, cone pattern formation, sward pattern tbrmation, T pattern formation, rectangle pattern formation and so on. We develop the user interface of the multi-robot system to program motion paths for variety pattern formation exchange according to the minimum displacement. In the experimental results, the supervised computer recognizes the various QR-code symbols using image system and decides which pattern formation to be selected on real-time. Mobile robots can receive the pattern formation command from the supervised computer, present the movement scenario from the original pattern formation to the assigned pattern formation on the motion platform, and avoid other mobile robots on real-time.
