# Comparing Computing Platforms for Deep Learning on a Humanoid Robot

arXiv: https://arxiv.org/abs/1809.03668 · HTML: https://mlsanity.com/paper/1809.03668/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 11 Sep 2018.

## Built on by (most cited first, 1 of 1)

- [Benchmarking Test-Time Unsupervised Deep Neural Network Adaptation on Edge Devices](https://mlsanity.com/paper/2203.11295/) (2022)

## Abstract (arXiv)

The goal of this study is to test two different computing platforms with respect to their suitability for running deep networks as part of a humanoid robot software system. One of the platforms is the CPU-centered Intel NUC7i7BNH and the other is a NVIDIA Jetson TX2 system that puts more emphasis on GPU processing. The experiments addressed a number of benchmarking tasks including pedestrian detection using deep neural networks. Some of the results were unexpected but demonstrate that platforms exhibit both advantages and disadvantages when taking computational performance and electrical power requirements of such a system into account.