tailieunhanh - Humanoid Robots Human-like Machines Part 17

Tham khảo tài liệu 'humanoid robots human-like machines part 17', kỹ thuật - công nghệ, cơ khí - chế tạo máy phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả | Hierarchical Reactive Control for Soccer Playing Humanoid Robots 631 most important object on the field we implemented a tracking procedure for it. If the ball could be detected in the previous frame a small window is placed at the predicted ball position. Only this window is analyzed for every frame. Every third frame is processed entirely to detect the other objects. The full frame is also processed if the vision system looses track of the ball. Fig. 4 illustrates a typical problem when processing images captured from a walking robot. The walking induces camera motion that causes motion blur in the image. Because the orange of the ball blends with the green carpet to a brownish color we use such a candidate color to detect blurred balls. In this case however it is important to make sure that a brownish color blob is surrounded by green carpet in order prevent false positive detections caused by brownish objects outside the field. a b Figure 4. The orange ball behind a white line on a green field. a Clean image captured from a standing robot. b Same situation with motion blur due to humanoid walking movements. The green blends with the orange to a brownish color Self-Localization The relative coordinates suffice for many relative behaviors like positioning behind the ball while facing the goal. To keep track of non-visible goals or to communicate about moving objects with other team members we need the robot coordinates in an allocentric frame x y -position on the field and orientation 0 . We solve self-localization by triangulation over pairs of landmark observations . detected goals and corner poles. When observing more than two landmarks the triangulation results are fused based on their confidence. Again the results of selflocalization are integrated over time and a motion model is applied. The lower-right of Fig. 3 illustrates the resulting allocentric representation. 3. Behavior Architecture We control the robots using a framework that supports a .

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