Figure 9. Path planning with algorithm of potential fields
Figure 9. Path planning with algorithm of potential fields
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Since the motion trajectory of each robot is divided into several median points that the robot should reach them one by one in a sequence the output obtained after the execution of AI will be a set of position and velocity vectors. So the task of the trajectory will be to guide the robots through the opponents to reach the destination. The routine used for this purpose is the potential field method (also an alternative new method is in progress which models the robot motion through opponents same as the flowing of a bulk of water through obstacles). In this method different electrical charges are assigned to our robots, opponents and the ball. Then by calculating the potential field of this system of charges a path will be suggested for the robot. At a higher level, predictions can be used to anticipate the position of the opponents and make better decisions in order to reach the desired vector. ; https://www.edusoft.ro/brain/index.php/brain/issue/view/5
Document information
Figure 9. Path planning with algorithm of potential fields
2010-04-02
BRAIN. Broad Research in Artificial Intelligence and Neuroscience 1(3) 57-64
Miscellaneous
Electronic Resource
English
| DDC: | 629 |
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