发表机构
Technische Universität Darmstadt（达姆施塔特工业大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
针对多旋翼平台空中操作中旋翼气流限制问题，提出基于优化的模块化空中机械手设计框架，联合考虑任务、末端执行器及气流约束，引入新分类与模型，通过重新配置优化适应多样任务需求，实验验证了框架有效性。
AI 中文摘要
多旋翼平台的空中操作能够在复杂环境中进行物理交互，但旋翼引起的气流仍然是涉及对气流敏感目标或周围环境的任务的关键限制。本文提出了一种基于优化的模块化空中机械手设计框架，该框架联合考虑了任务扳手可行性、末端执行器放置和气流暴露约束。我们首先引入了目标侧气流容忍度的新分类，并将相应的暴露要求表述为几何约束。为了有效地模拟旋翼引起的气流，我们引入了一个紧凑的锥球包络，它近似四旋翼气流的扩散结构，同时保持优化的计算可处理性。在此基础上，我们提出了一种重新配置优化方法，使模块化空中机械手适应不同的任务扳手要求，同时执行目标侧气流暴露和平台内气流干扰约束。与先前假设固定末端执行器位置的设计不同，所提出的框架优化了末端执行器放置以及平台配置。扩展性实验和消融研究验证了所提出框架的有效性。
英文摘要
Aerial manipulation with multirotor platforms enables physical interaction in complex environments, but rotor-induced airflow remains a critical limitation for tasks involving airflow-sensitive targets or surroundings. This paper presents an optimization-based design framework for modular aerial manipulators that jointly considers task wrench feasibility, end-effector placement, and airflow exposure constraints. We first introduce a novel categorization of target-side airflow tolerance and formulate the corresponding exposure requirements as geometric constraints. To efficiently model rotor-induced airflow, we introduce a compact cone-sphere envelope that approximates the spreading structure of a quadrotor's airflow while preserving computational tractability for optimization. Building on this formulation, we propose a reconfiguration optimization that adapts a modular aerial manipulator to diverse task wrench requirements while enforcing both target-side airflow exposure and intra-platform airflow interference constraints. Unlike prior designs that assume a fixed end-effector location, the proposed framework optimizes the end-effector placement together with the platform configuration. Scalability experiments and ablation studies validate the effectiveness of the proposed framework.
CommentsAccepted to the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2026
