Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Performance Improvement of Multi-Robot Data Transmission in Aggregated Robot Processing Architecture With Caches and QoS Balancing Optimization

Version 1 : Received: 3 May 2023 / Approved: 8 May 2023 / Online: 8 May 2023 (03:26:34 CEST)

A peer-reviewed article of this Preprint also exists.

Jalil, A.; Kobayashi, J.; Saitoh, T. Performance Improvement of Multi-Robot Data Transmission in Aggregated Robot Processing Architecture with Caches and QoS Balancing Optimization. Robotics 2023, 12, 87. Jalil, A.; Kobayashi, J.; Saitoh, T. Performance Improvement of Multi-Robot Data Transmission in Aggregated Robot Processing Architecture with Caches and QoS Balancing Optimization. Robotics 2023, 12, 87.

Abstract

Robot Operating System 2 (ROS 2) is a robotic software that uses a set of Quality of Service (QoS) policies to manage the quality of robot data transmissions in a network, such as the RELIABLE and KEEP_LAST options. In ROS 2 node communication, the RELIABLE connection guarantees that all message data can be properly sent from the publisher to the subscriber. However, strict reliability is not guaranteed if the RELIABLE connection uses the KEEP_LAST option to transmit the robot data in the publish-subscribe communication. This study aims to analyze the efficiency of local cache, cache control, and QoS balancing optimization to improve ROS 2 node communication when using the RELIABLE and KEEP_LAST options to transmit multi-robot data in Aggregated Robot Processing (ARP) architecture. Our idea in local cache and cache control is to streamline the sensor data output before processing it when the sensor device produces the data with the same value in a row. Furthermore, QoS balancing optimization aims to balance the DEPTH and DEADLINE QoS configuration to determine the rates and buffer size in ROS 2 node communication. This study shows that combining local cache and QoS balancing optimization improves multi-robot data transmission and cooperation in ARP architecture.

Keywords

Multi-Robot; Aggregated Robot Processing; Caches; QoS; Optimization; ROS 2

Subject

Computer Science and Mathematics, Robotics

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