HERO: Accelerating Autonomous Robotic Tasks with FPGA
Xuesong Shi, Lu Cao, Dawei Wang, Ling Liu, Ganmei You, Shuang Liu, Chunjie Wang
Abstract
The Heterogeneous Extensible Robot Open (HERO) platform is designed for autonomous robotic research. While bringing in the flexible computational capacities by CPU and FPGA, it addresses the challenges of heterogeneous computing by embracing OpenCL programming. We propose heterogeneous computing approaches for three fundamental robotic tasks: simultaneous localization and mapping (SLAM), motion planning and convolutional neural network (CNN) inference. With FPGA acceleration, the SLAM and motion planning tasks are performed 2–4 times faster on the HERO platform against fine-tuned software implementation. For CNN inference, it can process 20–30 images per second with the network of VGG-16 or ResNet-50. We expect the open platform and the developing experiences shared in this paper can facilitate future robotic research, especially for those compute intensive tasks of perception, movement and manipulation.
BibTeX
@inproceedings{iros2018_heroaccelerating,
title = {HERO: Accelerating Autonomous Robotic Tasks with FPGA},
author = {Xuesong Shi and Lu Cao and Dawei Wang and Ling Liu and Ganmei You and Shuang Liu and Chunjie Wang},
booktitle = {IROS 2018},
year = {2018}
}