arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 1802.08359cs.RO
收藏

PIRT:一个异构体系结构上的节能实时的机器人应用的框架

PIRT: A Runtime Framework to Enable Energy-Efficient Real-Time Robotic Applications on Heterogeneous Architectures

University of California, Santa Barbara(加州大学圣巴巴拉分校);PerceptIn Inc.(普思英公司);South China University of Technology(华南理工大学)

Liu Liu, Shaoshan Liu, Zhe Zhang, Bo Yu, Jie Tang, Yuan Xie

摘要:

在具有严格资源和能源限制的移动系统上实现具有不同行为的完整机器人工作负载仍然是一项挑战。近年来,已经尝试部署基于单加速器的计算平台(如GPU、DSP或FPGA)来解决这一挑战,但收效甚微。核心问题有两个方面:首先,不同的机器人任务需要不同的加速器,其次,同时管理多个加速器对开发人员来说是压倒性的。在本文中,我们提出了PIRT,这是第一个机器人运行时框架,可以有效地管理具有多个加速器的移动系统以及云上的动态任务执行,以实现更好的性能和节能。通过PIRT,我们使机器人能够同时执行25 FPS定位的自主导航,3 FPS的障碍物检测,路线规划,大型地图生成和场景理解,以每小时5英里的最高速度行驶,所有这些都在11 W的计算能力范围内。

英文摘要:

Enabling full robotic workloads with diverse behaviors on mobile systems with stringent resource and energy constraints remains a challenge. In recent years, attempts have been made to deploy single-accelerator-based computing platforms (such as GPU, DSP, or FPGA) to address this challenge, but with little success. The core problem is two-fold: firstly, different robotic tasks require different accelerators, and secondly, managing multiple accelerators simultaneously is overwhelming for developers. In this paper, we propose PIRT, the first robotic runtime framework to efficiently manage dynamic task executions on mobile systems with multiple accelerators as well as on the cloud to achieve better performance and energy savings. With PIRT, we enable a robot to simultaneously perform autonomous navigation with 25 FPS of localization, obstacle detection with 3 FPS, route planning, large map generation, and scene understanding, traveling at a max speed of 5 miles per hour, all within an 11W computing power envelope.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

↑