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Development of a Low-Level Control System Based on PID and RPM Imbalance Correction for Swarm Robotics
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Authors
Cang, Alexander
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Politeknik Negeri Batam
Abstract
Swarm robots are robotic systems capable of coordinated movement in formation patterns, with roles divided into leader and follower robots. Motor speed imbalance and trajectory deviations in differential drive mobile robots can lead to position and orientation errors, negatively affecting the accuracy of target motion. This study aims to design a motor speed control system that combines a Proportional–Integral–Derivative (PID) controller with an RPM imbalance correction method, along with odometry-based evaluation of individually controlled robots. Experimental results from motor characterization using encoders indicate motor speed variations below 5%. Testing three PID parameter configurations identified an optimal setting capable of maintaining stable motor speed, while the RPM imbalance correction method successfully maintained motor speed within the range of 49–51 RPM relative to the 50 RPM target, with errors below 1%, reduced overshoot, and faster settling time. Odometry-based evaluation during triangular and square formation tests showed average distance and orientation errors below 2%, demonstrating that the proposed control system effectively improves motion stability and accuracy.
Description
This study develops a differential-drive motor speed control system for swarm robots using DC motors and encoder sensors by integrating a Proportional–Integral–Derivative (PID) controller with an RPM imbalance correction method and odometry-based evaluation. Motor characterization shows inter-motor speed variations below 5%, allowing effective compensation through the proposed control strategy. Testing of three PID parameter sets identified an optimal configuration that ensured stable motor speed control. The RPM imbalance correction maintained motor speeds within 49–51 RPM for a 50 RPM target, achieving errors below 1% while reducing overshoot and settling time.
Formation experiments using triangular and square patterns demonstrated average position and orientation errors below 2%, confirming reliable coordination and formation stability. Overall, the combined PID and RPM imbalance correction approach improves motor speed stability and motion accuracy, showing strong potential for multi-robot applications requiring precise coordination. Future work will focus on enhancing position estimation using additional sensors such as IMUs, applying adaptive or intelligent control methods, and extending validation to larger robot groups and more complex formation and obstacle-avoidance scenarios.
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IEEE
