The Journal of Korea Robotics Society (로봇학회논문지)

Korea Robotics Society (한국로봇학회)
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Rate-Controlled Data-Driven Real-Time Stream Processing for an Autonomous Machine

자율 기기를 위한 속도가 제어된 데이터 기반 실시간 스트림 프로세싱

  • Noh, Soonhyun (Electrical and Computer Engineering Department, Seoul National University) ;
  • Hong, Seongsoo (Electrical and Computer Engineering Department, Seoul National University) ;
  • Kim, Myungsun (IT Convergence Engineering Department, Hansung University)
  • Received : 2019.10.02
  • Accepted : 2019.10.29
  • Published : 2019.11.30
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Abstract

Due to advances in machine intelligence and increased demands for autonomous machines, the complexity of the underlying software platform is increasing at a rapid pace, overwhelming the developers with implementation details. We attempt to ease the burden that falls onto the developers by creating a graphical programming framework we named Splash. Splash is designed to provide an effective programming abstraction for autonomous machines that require stream processing. It also enables programmers to specify genuine, end-to-end timing constraints, which the Splash framework automatically monitors for violation. By utilizing the timing constraints, Splash provides three key language semantics: timing semantics, in-order delivery semantics, and rate-controlled data-driven stream processing semantics. These three semantics together collectively serve as a conceptual tool that can hide low-level details from programmers, allowing developers to focus on the main logic of their applications. In this paper, we introduce the three-language semantics in detail and explain their function in association with Splash's language constructs. Furthermore, we present the internal workings of the Splash programming framework and validate its effectiveness via a lane keeping assist system.

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