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Path Optimization for Cluster Order Picking in Warehouse Robotics Using Hybrid Symbolic Control and Bio-Inspired Metaheuristic Approaches.

Biomimetics (Basel, Switzerland)·2025
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Task Scheduling of Multiple Humanoid Robot Manipulators by Using Symbolic Control.

Mete Özbaltan1, Nihan Özbaltan2, Hazal Su Bıçakcı Yeşilkaya1

  • 1Department of Electrical and Electronics Engineering, Faculty of Engineering and Architecture, İzmir Bakırçay University, 35665 İzmir, Türkiye.

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Summary

This study introduces a novel framework for scheduling tasks for multiple humanoid robot manipulators using symbolic discrete controller synthesis. The approach enhances production throughput and efficiency in complex industrial settings.

Keywords:
ANNhumanoid robot manipulatorsinverse kinematicsmultiple degrees of freedomoptimization algorithmssymbolic discrete controller synthesistask scheduling

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Area of Science:

  • Robotics
  • Control Systems
  • Artificial Intelligence

Background:

  • Coordinating multiple humanoid robot manipulators in industrial settings presents significant challenges in task scheduling.
  • Complexity arises from resource sharing, real-time decision-making, and inter-robot coordination.

Purpose of the Study:

  • To propose a framework for modeling and managing task scheduling for multiple humanoid robot manipulators.
  • To enhance system safety, enforce strict rules, and ensure mutual exclusion over shared resources.
  • To optimize production throughput and efficiency.

Main Methods:

  • Utilized symbolic discrete controller synthesis technique for task scheduling.
  • Encoded the task scheduling problem as discrete events using parallel synchronous dataflow equations.
  • Addressed the inverse kinematics for six-degree-of-freedom (6-DOF) robot arms using biomimetic metaheuristic approaches.

Main Results:

  • Experimental validation demonstrated high accuracy and performance of the proposed framework.
  • Achieved an average efficiency improvement of 40% in 70-robot systems, 20% in 30-robot systems, and 10% in 10-robot systems.
  • Significant increase in production throughput compared to systems without a controller.

Conclusions:

  • The proposed framework effectively manages task scheduling for multiple humanoid robot manipulators.
  • Symbolic discrete controller synthesis offers a robust solution for complex robotic coordination problems.
  • The approach leads to substantial improvements in industrial automation efficiency and productivity.