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<p>For emulating in-space missions using ground-based robotics, the authors have developed a 12-degrees-of-freedom (DoF) spacecraft simulator employing a hybrid mechanism that combines a 6-DoF robotic arm mounted on a 6-DoF Stewart platform. The redundancy offered by this 12-DoF system enables flexibility in achieving secondary mission objectives, such as joint-limit, singularity, and collision avoidance, alongside trajectory tracking. However, traditional robot planning and control methods are limited in their ability to address multiple tasks simultaneously. This work proposes an extension of the fuzzy logic-aided inverse kinematics (FLIK) control framework for this robotic system. FLIK enables simultaneous task execution in both joint and task spaces while ensuring minimum energy consumption by dynamically prioritizing among multiple secondary tasks in real time. This paper presents the dynamic modeling of the integrated system, outlines the conventional control strategies used for comparison, and details the architecture of the proposed FLIK controller. Performance is validated through extensive Monte Carlo simulations with variations in initial conditions, trajectories, and obstacle locations, confirming FLIK’s robustness and effectiveness in constraint-rich scenarios.</p>

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Fuzzy Logic-Based Multi-task Control of a Redundant Robotic Spacecraft Simulator

  • 期刊论文

  • 发表日期：

    2026年1月31日

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  • Anirudh Chhabra,
  • Donghoon Kim

摘要

For emulating in-space missions using ground-based robotics, the authors have developed a 12-degrees-of-freedom (DoF) spacecraft simulator employing a hybrid mechanism that combines a 6-DoF robotic arm mounted on a 6-DoF Stewart platform. The redundancy offered by this 12-DoF system enables flexibility in achieving secondary mission objectives, such as joint-limit, singularity, and collision avoidance, alongside trajectory tracking. However, traditional robot planning and control methods are limited in their ability to address multiple tasks simultaneously. This work proposes an extension of the fuzzy logic-aided inverse kinematics (FLIK) control framework for this robotic system. FLIK enables simultaneous task execution in both joint and task spaces while ensuring minimum energy consumption by dynamically prioritizing among multiple secondary tasks in real time. This paper presents the dynamic modeling of the integrated system, outlines the conventional control strategies used for comparison, and details the architecture of the proposed FLIK controller. Performance is validated through extensive Monte Carlo simulations with variations in initial conditions, trajectories, and obstacle locations, confirming FLIK’s robustness and effectiveness in constraint-rich scenarios.