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Adaptive control system of an insect brain during odor source localization

机译:气味源定位过程中昆虫大脑的自适应控制系统

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To realize an autonomous odor source localization robot, we focused on the adaptability of an insect¶s brain to compensate for rotational disturbances during odor source searching behavior. We manipulated motor outputs to control the sensory feedback of an insect using a brain-machine hybrid system. This system is composed of an insect¶s head and a two-wheeled mobile robot. The velocity of the robot is proportional to neural activities descending from an insect brain. We successfully manipulated the behavior of the robot. In disturbance experiments, insects responded to given rotational disturbances by modifying their neural activities to make compensative angular velocity. We assumed this control system of the compensation as an output-error model. We calculated the parameters under different motor gains to reveal it as an adaptive controller. We propose that an insect has its appropriate angular velocity during odor source localization, and performed simulation experiments involving an odor source searching agent and odor distribution environment. We calculated the cost for odor source localization by changing the angular velocity of the agent, and found that it had the minimum value.
机译:为了实现自主的气味源定位机器人,我们专注于昆虫大脑的适应性,以补偿气味源搜索行为期间的旋转干扰。我们使用脑机混合系统操纵电机输出以控制昆虫的感觉反馈。该系统由一个昆虫的头和一个两轮移动机器人组成。机器人的速度与昆虫脑部的神经活动成正比。我们成功地操纵了机器人的行为。在干扰实验中,昆虫通过改变其神经活动以补偿角速度来响应给定的旋转干扰。我们将这种补偿控制系统假定为输出误差模型。我们计算了不同电动机增益下的参数,以将其显示为自适应控制器。我们建议昆虫在气味源定位过程中具有适当的角速度,并进行了涉及气味源搜索剂和气味分布环境的模拟实验。我们通过改变试剂的角速度来计算气味源定位的成本,并发现它具有最小值。

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