Grasp planning and motion synthesis for dexterous manipulation tasks are traditionally done given a pre-existing kinematic model for the robotic hand. In this paper, we introduce a framework for automatically designing hand topologies best suited for manipulation tasks given high-level objectives as input. Our pipeline is capable of building custom hand designs around specific manipulation tasks based on high-level user input. Our framework comprises of a sequence of trajectory optimizations chained together to translate a sequence of objective poses into an optimized hand mechanism along with a physically feasible motion plan involving both the constructed hand and the object. We demonstrate the feasibility of this approach by synthesizing a series of hand designs optimized to perform specified in-hand manipulation tasks of varying difficulty. We extend our original pipeline 32 to accommodate the construction of hands suitable for multiple distinct manipulation tasks as well as provide an in depth discussion of the effects of each non-trivial optimization term.

中文翻译：

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用于手动操作任务的机器人手的自动化设计

传统上，在给定机器人手的预先存在的运动学模型的情况下，完成灵巧操作任务的抓取规划和运动合成。在本文中，我们介绍了一个框架，用于自动设计最适合操作任务的手部拓扑结构，并将高级目标作为输入。我们的管道能够基于高级用户输入围绕特定操作任务构建自定义手部设计。我们的框架包括一系列链接在一​​起的轨迹优化，以将一系列目标姿势转换为优化的手部机构，以及涉及构建的手部和对象的物理上可行的运动计划。我们通过综合一系列手部设计来证明这种方法的可行性，这些手部设计经过优化以执行不同难度的指定手部操作任务。32以适应适合多种不同操作任务的手结构，并深入讨论每个非平凡优化项的影响。