OMPL中的規劃算法彙總

OMPL簡介

• The Open Motion Planning Library(OMPL)是基於採樣方法的開源運動規劃庫，其規劃算法可以分爲兩類：
• Geometric planners
• Control-based planners

特性：基於採樣，概率完備，非最優/漸進最優

Move it!和OMPL的關係：

• OMPL is a open source library for sampling based / randomized motion planning algorithms. Sampling based algorithms are probabilistically complete: a solution would be eventually found if one exists, however non-existence of a solution cannot be reported. These algorithms are efficient and usually find a solution quickly. OMPL does not contain any code related to collision checking or visualization as the designers of OMPL did not want to tie it to a any particular collision checker or visualization front end. The library is designed so it can be easily integrated into systems that provide the additional components. MoveIt! integrates directly with OMPL and uses the motion planners from OMPL as its default set of planners. The planners in OMPL are abstract; i.e. OMPL has no concept of a robot. Instead, MoveIt! configures OMPL and provides the back-end for OMPL to work with problems in Robotics.

1. Geometric planners

1.1 Multi-query planners

• Probabilistic RoadmaMethod (PRM)
  • LazyPRM
  • PRM*
  • LazyPRM*
• SPArse Roadmap Spanner algorithm (SPARS)
• SPARS2

1.2 Single-query planners

• Rapidly-exploring Random Trees (RRT) 非最優
  • RRT Connect (RRTConnect)
  • RRT*
  • Lower Bound Tree RRT (LBTRRT)
  • Sparse Stable RRT(SST)
  • Transition-based RRT (T-RRT)
  • Vector Field RRT(VF-RRT)
  • Parallel RRT (pRRT)
  • Lazy RRT (LazyRRT)
• Expansive Space Trees (EST)
  • Single-query Bi-directional Lazy collision checking planner (SBL)
  • Parallel Single-query Bi-directional Lazy collision checking planner (pSBL)
• Kinematic Planning by Interior-Exterior Cell Exploration (KPIECE)
  • Bi-directional KPIECE (BKPIECE)
  • Lazy Bi-directional KPIECE (LBKPIECE)
• Search Tree with Resolution Independent Density Estimation (STRIDE)
• Path-Directed Subdivision Trees (PDST)
• Fast Marching Tree algorithm (FMT∗)
• Bidirectional Fast Marching Tree algorithm (BFMT∗)

1.3 Optimizing planners

• PRM*
• LazyPRM*
• RRT* 漸進最優
• RRT#
• RRTX
• Informed RRT*
• Batch Informed Trees (BIT*)
• Lower Bound Tree RRT (LBTRRT)
• Sparse Stable RRT(SST)
• Transition-based RRT (T-RRT)
• SPARS
• SPARS2
• FMT*
• CForest
• AnytimePathShortening (APS)

2. Control-based planners

These planners rely on state propagation rather than simple interpolation to generate motions.

• Rapidly-exploring Random Trees (RRT)
• Sparse Stable RRT(SST)
• Expansive Space Trees (EST)
• Kinodynamic Planning by Interior-Exterior Cell Exploration (KPIECE)
• Path-Directed Subdivision Trees (PDST)
• Syclop
  • Syclop using RRT as the low-level planner
  • Syclop using EST as the low-level planner
• Linear Temporal Logical Planner (LTLPlanner)