# Enhancements to the DIDO Optimal Control Toolbox

arXiv: https://arxiv.org/abs/2004.13112 · HTML: https://mlsanity.com/paper/2004.13112/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 27 Apr 2020.

## Built on by (most cited first, 1 of 1)

- [Data-driven Fuzzy Control for Time-Optimal Aggressive Trajectory Following](https://mlsanity.com/paper/2504.06500/) (2025)

## Abstract (arXiv)

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.