arXiv:2412.07556cs.ROcs.MS2024-12被引 1

用精密制造与优化算法,减少软硬混合夹爪的试错次数。

Optimization-Driven Design of Monolithic Soft-Rigid Grippers

  • 结合高精度制造技术与优化算法,降低制造误差。
  • 显著减少原型迭代次数,提升开发效率。
  • 适合需快速落地的软体机器人研发团队。

由于3D打印和模具成型等常见制造工艺带来的不可预测性,软体机器人的仿真到现实(sim-to-real)迁移仍是重大挑战。这些工艺常导致实际制件与仿真设计存在偏差,需多次试制才能获得可用系统。本文提出一种新方法,融合先进快速原型技术和高效优化策略。首先,采用通常用于刚性结构的快速原型技术,利用其高精度制造柔性组件,减少制造误差。其次,优化框架有效降低对大量原型的需求,大幅缩短迭代周期。该方法能识别出在现有制造能力下更可行、更实用的刚度参数。实验表明,该方法显著提升了原型开发效率,同时保持了预期性能。本研究推动了软体机器人领域仿真与现实之间的鸿沟弥合,为软体机器人系统的快速可靠部署铺平道路。

原文摘要 · Abstract (English)

Sim-to-real transfer remains a significant challenge in soft robotics due to the unpredictability introduced by common manufacturing processes such as 3D printing and molding. These processes often result in deviations from simulated designs, requiring multiple prototypes before achieving a functional system. In this study, we propose a novel methodology to address these limitations by combining advanced rapid prototyping techniques and an efficient optimization strategy. Firstly, we employ rapid prototyping methods typically used for rigid structures, leveraging their precision to fabricate compliant components with reduced manufacturing errors. Secondly, our optimization framework minimizes the need for extensive prototyping, significantly reducing the iterative design process. The methodology enables the identification of stiffness parameters that are more practical and achievable within current manufacturing capabilities. The proposed approach demonstrates a substantial improvement in the efficiency of prototype development while maintaining the desired performance characteristics. This work represents a step forward in bridging the sim-to-real gap in soft robotics, paving the way towards a faster and more reliable deployment of soft robotic systems.

软体机器人制造优化原型设计

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