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Bio-Inspired Metaheuristics for Time-Optimal Trajectory Planning in Cooperative Dual-Arm Bimanipulation.

Mario Peñacoba-Yagüe1, Jesús-Enrique Sierra-García1, Matilde Santos-Peñas2

  • 1Department of Digitalization, University of Burgos, 09001 Burgos, Spain.

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Summary

This study optimized dual-arm robot movements for efficient, collision-free tasks. Particle Swarm Optimization (PSO) proved fastest, achieving the shortest cooperative motion time.

Keywords:
bio-inspired metaheuristicscollision avoidancecooperative dual-arm manipulationindustrial roboticstime-optimal trajectory planning

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Area of Science:

  • Robotics and Automation
  • Computational Intelligence
  • Operations Research

Background:

  • Cooperative manipulation by dual-arm robots is crucial for complex industrial tasks.
  • Generating time-efficient and collision-free trajectories in constrained environments remains challenging.
  • Existing methods often struggle with balancing safety and speed in bimanipulation.

Purpose of the Study:

  • To develop a method for generating time-efficient, collision-free cooperative motions for dual-arm robots.
  • To investigate the performance of bio-inspired metaheuristics in solving constrained bimanipulation problems.
  • To compare the effectiveness of Particle Swarm Optimization (PSO), Whale Optimization Algorithm (WOA), and Gazelle Optimization Algorithm (GOA) for trajectory generation.

Main Methods:

  • Formulated trajectory generation as a constrained optimization problem.
  • Employed a safety-first cost function prioritizing collision avoidance before minimizing execution time.
  • Utilized bio-inspired metaheuristics (PSO, WOA, GOA) to solve the optimization problem.

Main Results:

  • All evaluated algorithms (PSO, WOA, GOA) successfully generated feasible cooperative trajectories.
  • Particle Swarm Optimization (PSO) demonstrated superior performance, achieving the shortest execution time (6.825 s).
  • PSO also exhibited earlier feasibility discovery and better final trajectory quality compared to WOA and GOA.

Conclusions:

  • An object-centric optimization methodology using bio-inspired metaheuristics is effective for constrained dual-arm bimanipulation.
  • A feasibility-first cost structure successfully separates safe motion discovery from time-optimal refinement.
  • PSO offers advantages in convergence speed and trajectory optimization for cooperative robotic tasks.