ALTRO: A Fast Solver for Constrained Trajectory Optimization
ALTRO: A Fast Solver for Constrained Trajectory Optimization
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DOI：
10.1109/iros40897.2019.8967788
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发表时间：
2019-11
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影响因子：
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通讯作者：
Taylor A. Howell;Brian E. Jackson;Zachary Manchester
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文献类型：
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作者：
Taylor A. Howell;Brian E. Jackson;Zachary Manchester
轨迹优化是机器人运动规划和控制中广泛使用的工具。针对这些问题的现有求解器要么依赖现成的非线性规划求解器，这些求解器在数值上稳健，能够处理任意约束，但由于是通用的，往往速度较慢；要么使用自定义数值方法，这些方法利用问题结构来提高速度，但往往缺乏稳健性，对约束的推理能力有限或没有。本文介绍了ALTRO（增广拉格朗日轨迹优化器），这是一种用于约束轨迹优化问题的求解器，它能处理一般的非线性状态和输入约束，并且由于对问题结构的精心利用，具有快速收敛性和数值稳健性。我们在一组基准运动规划问题上展示了它的性能，并与采用大规模序列二次规划和内点求解器的标准直接配置方法进行了比较。
Trajectory optimization is a widely used tool for robot motion planning and control. Existing solvers for these problems either rely on off-the-shelf nonlinear programming solvers that are numerically robust and capable of handling arbitrary constraints, but tend to be slow because they are general purpose; or they use custom numerical methods that take advantage of the problem structure to be fast, but often lack robustness and have limited or no ability to reason about constraints. This paper presents ALTRO (Augmented Lagrangian TRajectory optimizer), a solver for constrained trajectory optimization problems that handles general nonlinear state and input constraints and offers fast convergence and numerical robustness thanks to careful exploitation of problem structure. We demonstrate its performance on a set of benchmark motion-planning problems and offer comparisons to the standard direct collocation method with large-scale sequential quadratic programming and interior-point solvers.