Strengthening Collaboration via Interlinked Skew Assessment and Rectification (ISAR) in Swarm Robotics
Muhammad Usman Hashmi, Anas Bilal, Muhammad Khurram Ehsan, Monir Abdullah, Abdulbasit A. Darem, Sahraoui Dhelim
IEEE Access
School of Computing
Abstract

Ensuring time synchronization among robotic agents in a IoT based swarm robotic system is crucial for smooth operations. This synchronization enables distributed data logging, coordination of algorithms, and synchronized event-driven interactions, which would be impossible without a shared time reference. Maintaining this synchronization is key to keeping data generated by robotic agents consistent and accurate. While various synchronization methods exist, they often require multiple timestamp exchanges or radio messages to address clock skew. This article introduces the Interlinked Skew Assessment and Rectification (ISAR) method. It also presents the Swarm Agent Singular (SAS) Timestamp which provides a cross layered approach to handle clock skew and phase inconsistencies. A SAS timestamp can calculate both clock skew offset and phase offset at the receiving node. The paper delves into ISAR’s mathematical intricacies which includes skew calculations and statistical analysis. MATLAB simulations and experiments with Texas Instruments TMS320C6713 DSP Starter Kits showcase ISAR’s effectiveness which demonstrates practical applicability. The results affirm that using one SAS timestamp instead of multiple timestamp exchanges is a viable approach for synchronizing robotic agents. This will eventually conserves computational resources within swarm network.