# Towards hardware Implementation of WTA for CPG-based control of a Spiking Robotic Arm

arXiv: https://arxiv.org/abs/2202.07064 · HTML: https://mlsanity.com/paper/2202.07064/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 14 Feb 2022.

## Built on by (most cited first, 2 of 2)

- [A Winner-Takes-All Mechanism for Event Generation](https://mlsanity.com/paper/2504.11374/) (2025)
- [A Neuromorphic Architecture for Scalable Event-Based Control](https://mlsanity.com/paper/2511.11924/) (2025)

## Abstract (arXiv)

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.