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Operation of the Collaborative Composite Manufacturing CCM System
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Safe coordination of robots in cyclic paths.

Adriano M C Rezende1, Vinicius M Gonçalves1, Luciano C A Pimenta1

  • 1Graduate Program in Electrical Engineering, Universidade Federal de Minas Gerais, Pampulha, Belo Horizonte, MG, Brazil.

ISA Transactions
|October 20, 2020
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Summary
This summary is machine-generated.

This study introduces a mixed integer linear programming (MILP) approach for coordinating multiple robots on intersecting paths. The method ensures collision-free movement by planning velocity profiles offline, enhancing robot coordination safety and efficiency.

Keywords:
Collision avoidanceMixed integer linear programmingMulti-robot systemsTrajectory planning

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Area of Science:

  • Robotics
  • Operations Research
  • Control Systems

Background:

  • Coordinating multiple robots on persistent, intersecting paths presents significant challenges.
  • Existing methods often rely on online collision avoidance, which can be inefficient and prone to failure.
  • Key factors like speed constraints, spatial separation, acceleration limits, and uncertainties are often overlooked.

Purpose of the Study:

  • To develop a robust, offline planning strategy for multi-robot coordination on closed, intersecting paths.
  • To address limitations in current literature by incorporating realistic robot dynamics and environmental factors.
  • To ensure persistent, collision-free movement without the need for online replanning.

Main Methods:

  • A mixed integer linear programming (MILP) formulation was developed for robot path and velocity profile planning.
  • The model incorporates minimum and maximum speed constraints, acceleration limits, and uncertainties in position and velocity.
  • Offline planning of velocity profiles was employed to preemptively avoid collisions.

Main Results:

  • Simulations involving up to 48 robots demonstrated the strategy's effectiveness and efficiency.
  • The formulation successfully handled minimum spatial separation requirements.
  • A real-world experiment with three e-puck robots validated the robustness of the proposed method.

Conclusions:

  • The MILP-based offline planning approach provides a reliable method for coordinating multiple robots on complex paths.
  • The strategy effectively addresses practical constraints and uncertainties, outperforming traditional online methods.
  • The demonstrated robustness in simulations and real-world experiments highlights its applicability in diverse robotic systems.