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Multi-Parameter Predictive Model of Mobile Robot's Battery Discharge for Intelligent Mission Planning in Multi-Robot

Bartosz Poskart¹, Grzegorz Iskierka¹, Kamil Krot¹

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

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|December 23, 2022

Summary

This study introduces a universal battery discharge model for autonomous mobile robots. The model predicts battery usage for mission scheduling, optimizing fleet operations and production plans.

Keywords:

AGV AMR autonomous mobile robots battery consumption logistics 4.0 predictive mission assignment predictive monitoring

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Area of Science:

Robotics and Automation
Operations Research
Energy Systems

Background:

Current battery management systems lack predictive capabilities for mission completion.
Existing state-of-charge calculations are insufficient for fleet-wide mission scheduling.
Autonomous mobile robot fleets require enhanced operational planning.

Purpose of the Study:

To develop a universal battery discharge model for autonomous mobile robots.
To enable accurate prediction of battery usage during scheduled missions.
To improve mission scheduling and fleet management for flexible production systems.

Main Methods:

Developing a universal battery discharge model.
Integrating key mission parameters into the model.
Utilizing the model for predictive battery usage analysis.

Main Results:

A universal battery discharge model was developed.
The model accurately predicts battery consumption over scheduled missions.
The model facilitates informed decisions on mission delegation and fleet size.

Conclusions:

The developed model is essential for effective mission scheduling in autonomous mobile robot fleets.
It enhances the efficiency of flexible production systems.
This approach optimizes resource allocation and ensures production plan accomplishment.