In this paper, a novel bio-inspired trajectory planning method is proposed for robotic sys-tems based on an improved bacteria foraging optimization algorithm (IBFOA) and an improved in-trinsic Tau jerk (named Tau-J*) ...
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In this paper, a novel bio-inspired trajectory planning method is proposed for robotic sys-tems based on an improved bacteria foraging optimization algorithm (IBFOA) and an improved in-trinsic Tau jerk (named Tau-J*) guidance strategy. Besides, the adaptive factor and elite-preservation strategy are employed to facilitate the IBFOA, and an improved Tau-J* with higher-order of intrinsic guidance movement is used to avoid the nonzero initial and final jerk, so as to overcome the computa-tional burden and unsmooth trajectory problems existing in the optimizationalgorithm and traditional interpolation algorithm. The IBFOA is utilized to determine a small set of optimal control points, and Tau-J* is then invoked to generate smooth trajectories between the control points. Finally, the results of simulation tests demonstrate the eminent stability, optimality, and rapidity capability of the proposed bio-inspired trajectory planning method.
In this paper, an improved bacteria foraging optimization algorithm based on different constraint conditions is proposed to solve the vehicle routing problem with pickup and delivery(VRPPD). At first, the mathematical...
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ISBN:
(纸本)9781510842304
In this paper, an improved bacteria foraging optimization algorithm based on different constraint conditions is proposed to solve the vehicle routing problem with pickup and delivery(VRPPD). At first, the mathematical model is established aiming at minimizing the dispatching time and the total cost. Secondly, the paper proposes the method with dynamic variable step factor, as well as propagation threshold and death threshold to copy the excellent individuals and eliminate the inferior individuals. Finally, the improved method is applied to the CMTn X and CMTn Y, and its effectiveness is verified from the result of comparison with some existing algorithms.
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