Topology optimization for multi-component robotic arms under time-varying loads

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Abstract
High structural performance of robotic arms is essential for positioning precision and energy efficiency in industrial applications. This study presents a design-dependent topology optimization framework for multi-component robotic arms, addressing dynamic multi-load scenarios during motion. Utilizing the Bi-directional Evolutionary Structural Optimization (BESO) method, the framework incorporates self-weight and inertial loads and takes into account the time-varying acceleration of serial robotic arms in a forward manner. The objective is to minimize mean compliance under a transient context. Three numerical examples, namely a 2D single robotic arm, a 3D two-arm in-plane rotation, and a 3D three-arm spatial movement, are presented to demonstrate the efficacy of the proposed framework. The optimization results highlight the necessity of considering design-dependent loads and different robotic configurations in topological evolution. Comparative studies on motion strategies and travel times further emphasize the importance of integrating structural performance with movement dynamics. This approach offers significant insights into the topological design of robotic arms, potentially improving their operational efficiency and precision in various industrial applications.
Funding Information
  • Australian Research Council (DP230103180)
  • The University of Newcastle

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