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首页> 外文期刊>Adaptive Behavior >Evolving the Neural Controller for a Robotic Arm Able to Grasp Objects on the Basis of Tactile Sensors
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Evolving the Neural Controller for a Robotic Arm Able to Grasp Objects on the Basis of Tactile Sensors

机译：基于触觉传感器的机械臂神经控制器的发展

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摘要

We describe the results of a set of evolutionary experiments in which a simulated robotic arm provided with a two-fingered hand has to reach and grasp objects with different shapes and orientations on the basis of simple tactile information. The results that we obtained are encouraging and demonstrate that the problem of grasping objects with characteristics that vary within a certain range can be solved by producing rather simple forms of behavior. These forms of behavior exploit emergent characteristics of the interaction between the body of the robot, its control system, and the environment. In particular we show that evolved individuals do not try to keep the environment stable, but rather push and pull the objects; thus, they produce a dynamic in the environment and exploit the interaction between the body of the robot and the dynamic environment to master different environmental conditions with similar control strategies.
机译：我们描述了一组进化实验的结果，在该实验中，配备有两只手的模拟机械臂必须在简单的触觉信息的基础上到达并抓住具有不同形状和方向的物体。我们获得的结果令人鼓舞，并表明，可以通过产生相当简单的行为形式来解决抓握特性在一定范围内变化的对象的问题。这些行为形式利用了机器人主体，其控制系统和环境之间相互作用的新兴特征。特别是，我们证明了进化的个体并不是试图保持环境的稳定，而是要推拉物体。因此，它们在环境中产生动态，并利用机器人的身体与动态环境之间的交互作用，以类似的控制策略来掌握不同的环境条件。

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