论文标题
基于测序的歧管基于采样的运动计划
Sampling-Based Motion Planning on Sequenced Manifolds
论文作者
论文摘要
我们解决了在受约束的配置空间中规划机器人运动的问题，在整个运动中，约束变化。该问题被表述为相交歧管的固定序列，机器人需要遍历该序列才能解决任务。我们指定了一类顺序运动计划问题，这些问题在歧管之间过渡时满足了自由配置空间中更改的特定属性。对于此问题类别，我们在测序的歧管（PSM*）上开发了算法计划，该计划通过在内部环中使用新颖的转向策略在内部环中使用RRT*之间搜索歧管之间的最佳相交点。我们提供了有关PSM*的概率完整性和渐近最优性的理论分析。此外，我们评估了其在多机器人对象运输任务上的计划绩效。 视频：https：//youtu.be/q8kbiltrxfu 代码：https：//github.com/etpr/sequential-manifold-planning
We address the problem of planning robot motions in constrained configuration spaces where the constraints change throughout the motion. The problem is formulated as a fixed sequence of intersecting manifolds, which the robot needs to traverse in order to solve the task. We specify a class of sequential motion planning problems that fulfill a particular property of the change in the free configuration space when transitioning between manifolds. For this problem class, we develop the algorithm Planning on Sequenced Manifolds (PSM*) which searches for optimal intersection points between manifolds by using RRT* in an inner loop with a novel steering strategy. We provide a theoretical analysis regarding PSM*s probabilistic completeness and asymptotic optimality. Further, we evaluate its planning performance on multi-robot object transportation tasks. Video: https://youtu.be/Q8kbILTRxfU Code: https://github.com/etpr/sequential-manifold-planning
