An adaptive three-dimensional space path planning method based on particle swarm optimization
A particle swarm algorithm and three-dimensional space technology, which is applied in the field of computational intelligence and can solve problems such as uneven optimal path, difficulty, and inability to complete path planning tasks.
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[0115] Starting point coordinate S=(11125015700-600); m end point coordinate D=(11260017210-600)m; population number n=10; particle node number m=42; maximum number of iterations k max =300; the upper and lower bounds of the displacement are respectively Among them, L=2272 is the larger value of the length and width of the m map; the inertia weight is based on the formula OK, where ω max = 0.9, ω min =0.4, k is the number of iterations; learning factor c 1 According to the formula c 1 = c 1 max - ( k k max ) u c · ( c 1 max - c 1 min ...
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