论文标题
朝着硬件实施WTA，以基于CPG的机器人臂控制
Towards hardware Implementation of WTA for CPG-based control of a Spiking Robotic Arm
论文作者
论文摘要
生物神经系统通常会控制许多自由度，例如在动物四肢中。神经形态工程师通过在硬件中模拟它们来研究这些系统，以深入了解及其在工程和机器人技术中解决复杂问题的可能应用。中央模式生成器（CPGS）是神经控制器的一部分，通常在其最后一步中使用，以产生肢体运动的节奏模式。不同的模式和步态通常会通过赢家 - 全部（WTA）电路竞争，以产生正确的动作。在这项工作中，我们介绍了在尖峰神经网络（SNN）处理器中实施的WTA电路，以实时产生这种模式，以实时控制机器人臂。该机器人使用基于尖峰的比例综合启动（SPID）控制器，以使WTA电路神经元的获胜者人口保持指挥的联合位置。实验证明了机器人对照在大脑启发后使用尖峰电路的可行性。
Biological nervous systems typically perform the control of numerous degrees of freedom for example in animal limbs. Neuromorphic engineers study these systems by emulating them in hardware for a deeper understanding and its possible application to solve complex problems in engineering and robotics. Central-Pattern-Generators (CPGs) are part of neuro-controllers, typically used at their last steps to produce rhythmic patterns for limbs movement. Different patterns and gaits typically compete through winner-take-all (WTA) circuits to produce the right movements. In this work we present a WTA circuit implemented in a Spiking-Neural-Network (SNN) processor to produce such patterns for controlling a robotic arm in real-time. The robot uses spike-based proportional-integrativederivative (SPID) controllers to keep a commanded joint position from the winner population of neurons of the WTA circuit. Experiments demonstrate the feasibility of robotic control with spiking circuits following brain-inspiration.
