Name
Title | ||
|---|---|---|
LaLo-Check: A Path Optimization Framework for Sampling-Based Motion Planning With Tree Structure. |
Abstract | ||
|---|---|---|
Motion planning is a basic problem in many areas, such as robotics, computer games, and animation. It is a challenge to generate a better solution in less time. Line-of-Sight (LoS) is the straight path between two points, and LoS-Check is often used as a path shortcutting method. Lazy evaluation is a successful strategy in reducing the amount of collision detection, which accelerates the motion planning algorithms, especially in high-dimensional spaces. In this paper, we present Lazy LoS-Check (LaLo-Check), which employs a lazy evaluation strategy with the help of a lower bound technique to delay the LoS-Check until it is necessary. The lower bound technique only accepts the states which could provide a better solution, and it is commonly applied in the sample rejection and candidate path selection. Actually, LaLo-Check can be considered as a general path optimization framework, which could be used in most tree-structure motion planners. We choose three representative sampling-based motion planning algorithms, RRT*, Informed RRT*, and BIT*, to evaluate the performance of LaLo-Check. The experimental results show that the new planners which employ the LaLo-Check could find better solutions than the original algorithms within the equivalent time. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/ACCESS.2019.2930634 | IEEE ACCESS |
Keywords | DocType | Volume |
Motion planning,line of sight,lazy evaluation,lower bound,path optimization | Journal | 7 |
ISSN | Citations | PageRank |
2169-3536 | 0 | 0.34 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Changwu Zhang | 1 | 0 | 0.34 |
| Li Zhou | 2 | 69 | 2.77 |
| Hengzhu Liu | 3 | 86 | 23.28 |