In 2020, DIDO$^\copyright$ turned 20! The software package emerged in 2001 as a basic, user-friendly MATLAB$^\circledR$ teaching-tool to illustrate the various nuances of Pontryagin's Principle but quickly rose to prominence in 2007 after NASA announced it had executed a globally optimal maneuver using DIDO. Since then, the toolbox has grown in applications well beyond its aerospace roots: from solving problems in quantum control to ushering rapid, nonlinear sensitivity-analysis in designing high-performance automobiles. Most recently, it has been used to solve continuous-time traveling-salesman problems. Over the last two decades, DIDO's algorithms have evolved from their simple use of generic nonlinear programming solvers to a multifaceted engagement of fast spectral Hamiltonian programming techniques. A description of the internal enhancements to DIDO that define its mathematics and algorithms are described in this paper. A challenge example problem from robotics is included to showcase how the latest version of DIDO is capable of escaping the trappings of a ``local minimum'' that ensnare many other trajectory optimization methods.

中文翻译：

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DIDO Optimal Control Toolbox 的增强功能

2020年，DIDO$^\copyright$ 20岁啦！该软件包于 2001 年作为基本的、用户友好的 MATLAB$^\circledR$ 教学工具出现，用于说明庞特里亚金原理的各种细微差别，但在 2007 年美国宇航局宣布已使用 DIDO 执行全球最佳机动后迅速崛起。从那时起，该工具箱的应用范围远远超出了其航空航天领域：从解决量子控制问题到在设计高性能汽车中引入快速非线性灵敏度分析。最近，它已被用于解决连续时间旅行商问题。在过去的二十年里，DIDO 的算法已经从简单使用通用非线性规划求解器发展为快速谱哈密顿规划技术的多方面参与。本文描述了定义其数学和算法的 DIDO 内部增强功能。包含一个来自机器人技术的挑战示例问题，以展示最新版本的 DIDO 如何摆脱“局部最小值”的陷阱，这些陷阱会诱捕许多其他轨迹优化方法。