CPU scheduling in robotics & AR/VR applications

Aditi, -

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https://hdl.handle.net/2142/110582 Copy

Description

Title

CPU scheduling in robotics & AR/VR applications

Author(s)

Aditi, -

Issue Date

2021-04-27

Director of Research (if dissertation) or Advisor (if thesis)

• Godfrey, Philip Brighten
• Mittal, Radhika

Department of Study

Computer Science

Discipline

Computer Science

Degree Granting Institution

University of Illinois at Urbana-Champaign

Degree Name

M.S.

Degree Level

Thesis

Date of Ingest

2021-09-17T01:13:29Z

Keyword(s)

• Robotics
• Scheduling
• Resource management
• AR/VR

Abstract

Robot and AR/VR systems have to take highly responsive real-time actions, driven by complex decisions involving a pipeline of sensing, perception, planning, and reaction tasks. Given constrained resources, this leads to a difficult scheduling problem. In practice – system designers manually tune params for their specific hardware and application, while real-time scheduling approaches assume static periodic schedules – both of which result in suboptimal application performance especially when both the environment and the hardware can change. In this work, we highlight the emerging need for automated resource optimization at runtime in sense-react systems. As a step towards this goal, we identify various unique challenges in this area, especially understanding the key scheduling requirements for such systems. We propose a preliminary framework and a novel scheduling policy that enables efficient and dynamic optimization of application-specific performance goals. In experiments with a prototype implemented in the ROS and ILLIXR platforms, we show that our approach improves application performance, for example, 15x better performance for a face tracking robot and 7x better collision avoidance for a navigation robot. We believe this work will lead to systems that are substantially easier to develop and fulfill their tasks measurably better.

Graduation Semester

2021-05

Type of Resource

Thesis

Permalink

http://hdl.handle.net/2142/110582

Copyright and License Information

Copyright 2021 - Aditi

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