An Evolutionary Artificial Potential Field Algorithm for Dynamic Path Planning of Mobile Robot
Citations
266 citations
199 citations
Cites background from "An Evolutionary Artificial Potentia..."
...[57] proposed a modified APF approach for the path planning of mobile robot in a dynamic environment....
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100 citations
Cites background or methods from "An Evolutionary Artificial Potentia..."
...In [36] the simulation results show that the proposed EAPF methodology is efficient and robust for robot path planning with non-stationary goals and obstacles, also in [32] a new EAPF method for MR path planning in a dynamic environment is proposed, in that work the target and the obstacles are mov-...
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...Figure 5a shows the case of having a local minima trap regardless it might exist a valid path to the target; in [32, 36, 38, 44], this problem was illustrated for different situations....
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...The interaction with the real world requires the ability to respond and taking decisions over the changes in the environment, in [12, 32, 35, 36] some implementations with changing environments (world configuration) are presented....
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78 citations
71 citations
Cites methods from "An Evolutionary Artificial Potentia..."
...We will discuss in detail the modelling of the environment, structure of the approach/algorithm, the generation of the initial feasible path, the new planner for generating the random path, and the procedure of the online computation....
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...Traditionally, the path length Ef is the evaluation criterion for the quality of the path solution derived from the algorithm....
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...The pseudo-code of the algorithm is as following: T = Tinitial; while (T > Tterminate) randomly generate one feasible solution Xs; evaluate Xs, Ef = f(Xs); count = 1; while (count < Threshold) generate a new feasible solution Xn base on Xs; evaluate Xn, En = f(Xn); if f(Xn) < f(Xs) Xs = Xn; else if…...
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References
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