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Additional info for 1996 IEEE International Conference on Systems, Man and Cybernetics
Nevertheless, the extension to 3D is not complicated. The obstacles are represented by straight lines or polygons. Adapting the Messy Genetic Algorithm for Path Planning 27 Table 1. A complete descriptions of the tests. 5) to (8,2) Figure of the found path 4 (6,2) 6 We present two tests with a planar robot. The links are represented by straight lines and revolute joints. The global reference of the robot is in the coordinates (0,0). 4 units. We must remember that in 2D a robot with 3 or more joints is considered redundant.
Here, we have chosen 4 classes which correspond to the main elements in our environment: grass, sky, tree and rock. Labels in the images indicate the nature of the regions: (R) rock, (G) grass, (T) tree and (S) sky. The coherence of the model is tested by using the topological characteristics of the environment. The Region at the top right corner of the image was identiﬁed as grass, however this region has a relatively low probability (less than a given threshold) of belonging to this class, in this case the system can correct the mistake by using contextual information.
Besides, a movement is the minimal information entity in the string (a gene). The crossing is carried out by a point obtained randomly in the string number one, and another randomly obtained point in the string number two. The crossing is performed in these points. Both the current individuals and the new ones can have a different length. The length of the string is proportional to the length of the path. This length is represented by the cardinality of the sequence of the neighbor configurations that compose the path.
1996 IEEE International Conference on Systems, Man and Cybernetics by IEEE