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Adaptive gait generation for hexapod robot using Genetic Algorithm

机译:使用遗传算法的Hexapod机器人的自适应步态生成

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Animals display naturally robust locomotion designs which enable them to move on rugged terrains and even adapt to injuries. Most of the robots do not possess such robustness and are rendered useless if they get structurally damaged. In this paper; it is shown that such adapting ability can be introduced in robot's locomotion; if damaged; by evolving optimal gaits through genetic algorithm (GA). A hexapod robot simulation was used to test the gaits generated by GA. Simulation results have proven that the evolved gait enables a hexapod to move effectively with one leg damaged. This technique will increase the reliability and effectiveness of autonomous robots in areas hostile to humans.
机译:动物展示了自然的强大的运动设计,使他们能够在坚固的地形上移动,甚至适应伤害。大多数机器人都没有这种稳健性,如果它们在结构上损坏,则无用。在本文中;结果表明,可以在机器人的运动中引入这种适应能力;如果损坏;通过遗传算法(GA)通过演变最佳Gaits。 Hexapod机器人仿真用于测试GA生成的GA。仿真结果证明了进化的步态使六角形能够有效地移动,一条腿损坏。这种技术将提高自主机器人在敌对的地区对人类的可靠性和有效性。

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