基于序列凸规划的非线性密度驱动多智能体覆盖最优控制
原标题：Nonlinear Density-Driven Optimal Control (D2OC) for Multi-Agent Spatial Coverage via Sequential Convex Programming
AI 摘要
该论文将密度驱动最优控制（D2OC）框架扩展到离散时间控制仿射非线性系统，用于多智能体空间覆盖任务。方法通过序列凸规划在每个控制步对非线性动力学进行局部线性化，求解严格凸二次规划，同时保留基于 Wasserstein 的覆盖目标与输入约束。作者推导了有限时域误差界，并在独轮车与四旋翼团队仿真中验证：覆盖性能与非线性模型预测控制相当，但计算时间显著降低。
正文节选
Nonlinear Density-Driven Optimal Control (D2OC) for Multi-Agent Spatial Coverage via Sequential Convex Programming Abstract This paper presents a nonlinear extension of Density-Driven Optimal Control (D2OC) for multi-agent spatial coverage with prescribed density distributions. Rather than assigning individual target locations, D2OC drives the collective spatial distribution of agents toward a desired density through a Wasserstein-based objective. We extend this framework to multi-step finite-ho