提出精确解法处理微分动态规划中的端点约束问题。
Endpoint-Explicit Differential Dynamic Programming via Exact Resolution
- 通过精确解析方法处理端点与阶段等式约束
- 保证二次收敛且能应对秩不足情况
- 适合机器人模型预测控制与优化求解加速
我们提出一种新方法，用于处理约束微分动态规划（DDP）中的端点约束。与现有方法不同，该方法保证二次收敛且为精确解，能有效处理端点和阶段等式约束中的秩不足问题。适用于前向与逆动力学形式，特别适合模型预测控制（MPC）应用，并可加速最优控制（OC）求解器。我们在多种机器人问题中验证了该方法的有效性，并在CROCODDYL中提供了用户友好的开源实现。
原文摘要 · Abstract (English)
We introduce a novel method for handling endpoint constraints in constrained differential dynamic programming (DDP). Unlike existing approaches, our method guarantees quadratic convergence and is exact, effectively managing rank deficiencies in both endpoint and stagewise equality constraints. It is applicable to both forward and inverse dynamics formulations, making it particularly well-suited for model predictive control (MPC) applications and for accelerating optimal control (OC) solvers. We demonstrate the efficacy of our approach across a broad range of robotics problems and provide a user-friendly open-source implementation within CROCODDYL.
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