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The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy

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Predictive Monitoring System for Autonomous Mobile Robots Battery Management Using the Industrial Internet of Things

Kamil Krot¹, Grzegorz Iskierka¹, Bartosz Poskart¹

¹Faculty of Mechanical Engineering, Wrocław University of Science and Technology, ul. Łukasiewicza 5, 50-371 Wrocław, Poland.

Materials (Basel, Switzerland)

|October 14, 2022

Summary

Researchers analyzed lithium NMC battery discharge in autonomous mobile robots. Consistent battery performance enables predictive monitoring for safer, more efficient in-house transportation.

Keywords:

AMR IIoT Node-RED automation stack autonomous mobile robot predictive monitoring

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Area of Science:

Robotics
Battery Technology
Predictive Maintenance

Background:

Autonomous mobile robots (AMRs) are increasingly used for in-house logistics.
Efficient battery management is crucial for AMR operational continuity.
Predictive models can optimize AMR task allocation and maintenance.

Purpose of the Study:

To analyze the discharge characteristics of lithium NMC batteries in AMRs.
To develop a predictive model for AMR battery states based on queued missions.
To enhance the safety and efficiency of in-house transportation systems.

Main Methods:

Discharge characteristic analysis of lithium NMC batteries under operational load.
Development and implementation of a predictive monitoring system for AMR state of charge.
Testing the system in simulated real-life scenarios with varying mission loads.

Main Results:

Lithium NMC battery discharge characteristics remained consistent across different mission types and durations.
The developed model accurately predicts future battery states.
The system effectively detects anomalies in robot paths and battery behavior.

Conclusions:

Consistent battery discharge allows for reliable predictive monitoring of AMRs.
Predictive systems enhance in-house transportation safety and efficiency.
Early anomaly detection aids maintenance and task delegation for AMRs.