机器人避障时可移动障碍物，找到局部最优解路径。
Locally Optimal Solutions to Constraint Displacement Problems via Path-Obstacle Overlaps
- 分两阶段：先找最优轨迹，再移动障碍物使其可行。
- 在两类不同问题中成功实现机器人无碰撞路径规划。
- 适合需动态调整环境的机器人路径规划场景。
我们提出一种统一方法，解决机器人通过移动约束或障碍物来寻找可行路径的约束位移问题。该方法采用两阶段流程：第一阶段在障碍物中计算一条最小化特定目标函数的轨迹；第二阶段将障碍物移动，使计算出的机器人轨迹变为可行（即无碰撞）。通过两个不同类别的约束位移问题实例，验证了该方法的有效性。
原文摘要 · Abstract (English)
We present a unified approach for constraint displacement problems in which a robot finds a feasible path by displacing constraints or obstacles. To this end, we propose a two stage process that returns locally optimal obstacle displacements to enable a feasible path for the robot. The first stage proceeds by computing a trajectory through the obstacles while minimizing an appropriate objective function. In the second stage, these obstacles are displaced to make the computed robot trajectory feasible, that is, collision-free. Several examples are provided that successfully demonstrate our approach on two distinct classes of constraint displacement problems.
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