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ROSCH:Real-Time Scheduling Framework for ROS | IEEE Conference Publication | IEEE Xplore

ROSCH:Real-Time Scheduling Framework for ROS


Abstract:

This paper presents a real-time scheduling framework for the robot operating system (ROS) called ROSCH. ROS is an open-source software platform and a meta-operating syste...Show More

Abstract:

This paper presents a real-time scheduling framework for the robot operating system (ROS) called ROSCH. ROS is an open-source software platform and a meta-operating system designed for robots. ROS provides extensive development libraries and has been widely used for autonomous driving systems. However, ROS does not guarantee real-time performance; hence, a ROS-based autonomous driving car could cause a traffic accident. Therefore, ROSCH comprises three functionalities that do not exist in the ROS to guarantee real-time performance: (1) a synchronization system, (2) fixed-priority based directed acyclic graph (DAG) scheduling framework, and (3) fail-safe function. In particular, the synchronization system guarantees that the timestamp gaps between sensor measurements will be less than or equal to the calculated value. The fixed-priority based DAG scheduling framework guarantees that end-to-end latency is less than or equal to an estimated value. Operating both mechanisms simultaneously guarantees the final output topic frequency. The fail-safe functionality provides a danger avoidance action at a deadline miss. In addition, these functionalities are designed to be compatible with legacy software. No previous method that guarantees real-time operation provides a comparable range of features while maintaining the compatibility with the existing software. Experimental results showed that the time differences between sensor timestamps remained below a calculated value. Moreover, correctly scheduled tasks incur an end-to-end latency that is within an estimated value. In addition, the throughput of the end node is achieved. Finally, the fail-safe functionality overhead is 45 μsec on an average, which is 0.004% of the average execution time for one node.
Date of Conference: 28-31 August 2018
Date Added to IEEE Xplore: 10 January 2019
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Conference Location: Hakodate, Japan

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