Exploiting Advanced Collision Detection Libraries in a Probabilistic Motion Planner
Exploiting Advanced Collision Detection Libraries in a Probabilistic Motion Planner
复制标题
在概率运动规划器中利用高级碰撞检测库
DOI：
--
复制
发表时间：
2002
期刊：
影响因子：
--
通讯作者：
Mirko Mazzoli
中科院分区：
文献类型：
--
作者：
S. Caselli;M. Reggiani;Mirko Mazzoli
运动规划是许多应用领域的基本问题，包括机器人、自动化和虚拟现实。运动规划的性能在很大程度上取决于底层的碰撞检测技术。在本文中，我们报告的结果，最近的碰撞检测库的刚性和关节式机器人的运动规划的背景下，在3D打印的实验评估。被调查的图书馆也是根据它们对研究界的免费可用性而选择的。本文报道的结果表明，一些碰撞检测包调查是非常敏感的类型的问题要解决的问题，可能会确定在某些问题上的最佳性能和证明是非常不有效的，甚至不适用于不同的问题。其他碰撞检测库对问题类型的敏感度要低得多，尽管它们不一定在任何给定问题上表现出最佳性能。这些考虑表明，运动规划器可以利用基于要解决的问题的特性在一系列碰撞检测库中选择一个的能力，所述特性可以是先验已知的。
Motion planning is a fundamental problem in a number of application areas, including robotics, automation, and virtual reality. The performance of motion planning is largely affected by the underlying collision detection technique. In this paper we report the results of an experimental evaluation of several recent collision detection libraries within the context of motion planning for rigid and articulated robots in 3D workspaces. The libraries investigated have been chosen based also on their free availability to the research community. Results reported in this paper show that some of the collision detection packages investigated are very sensitive to the type of problem to be solved, possibly determining the best performance on certain problems and proving very inefficient or even not applicable on different problems. Other collision detection libraries are much less sensitive to the type of problem, although they do not necessarily exhibit the best performance on any given problem. These considerations suggest that a motion planner could take advantage from the ability to select one among a range of collision detection libraries based on characteristics of the problem to be solved which could be known a priori.