首页> 外文会议>Conference on optomechatronic systems >Cellular Neural Networks and Biologically inspired motion control
【24h】

Cellular Neural Networks and Biologically inspired motion control

机译:细胞神经网络和生物启发运动控制

获取原文

摘要

The main purpose of this paper is to present the Cellular Neural Network (CNN) Paradigm as a powerful strategy to design and to implement in hardware efficient locomotion control techniques. A gallery of biologically inspired walking robots are presented. Moreover, the availability of efficient distributed control structures needs a sensing capability of the same efficiency. Therefore the sensing stage is performed by using once againt eh CNN paradigm, but used as fast image processors. The strategy is supported by the fact that CNN devices with on-chip optical sensors are currently being tested and will be soon available. In such a way, images are acquired by a video camera with a CNN image processing device, able to extract the key features. These ones represent the "command" to take on the right locomotion pattern. Since all the methodology is realized by using alalog processors, the whole strategy represented a real breakthrough in the smart sensing and control field.
机译:本文的主要目的是将蜂窝神经网络(CNN)范例作为设计的强大策略,并在硬件有效的机器人控制技术中实现。提供了一个生物启发行走机器人的画廊。此外,有效分布式控制结构的可用性需要具有相同效率的感测能力。因此,通过使用一次AGAINT EH CNN范式来执行感测阶段,但用作快速图像处理器。该策略得到了当前正在测试有片上光学传感器的CNN设备,并且很快就会提供。以这种方式,通过具有CNN图像处理设备的摄像机获取图像,能够提取关键特征。这些代表了采取正确运动模式的“命令”。由于所有方法都是通过使用Alalog处理器实现的,因此整个策略代表了智能传感和控制领域的实际突破。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号