论文标题
本地规划师长凳：本地运动计划的基准测试
Local Planner Bench: Benchmarking for Local Motion Planning
论文作者
论文摘要
本地运动计划是机器人技术领域的大量研究主题，每年都会发表许多有希望的算法。但是，比较现场的不同方法是困难且耗时的。在本文中，我们提出了LocalPlannerBench，这是一个新的基准测试套件，可以在本地运动计划算法之间进行快速无缝的比较。该项目的重点在于环境和仿真案例的可扩展性。开箱即用，LocalPlannerBench已经支持许多模拟案例，从简单的2D点质量到成熟的3D 7DOF操纵器，使用URDF文件添加您自己的自定义机器人，这一点很简单。后处理器是内置的，可以通过自定义指标和图扩展。要整合您自己的运动计划者，只需创建一个从提供的基类衍生的包装器即可。最终，我们旨在提高本地运动计划算法的可重复性，并鼓励标准化的开源比较。
Local motion planning is a heavily researched topic in the field of robotics with many promising algorithms being published every year. However, it is difficult and time-consuming to compare different methods in the field. In this paper, we present localPlannerBench, a new benchmarking suite that allows quick and seamless comparison between local motion planning algorithms. The key focus of the project lies in the extensibility of the environment and the simulation cases. Out-of-the-box, localPlannerBench already supports many simulation cases ranging from a simple 2D point mass to full-fledged 3D 7DoF manipulators, and it is straightforward to add your own custom robot using a URDF file. A post-processor is built-in that can be extended with custom metrics and plots. To integrate your own motion planner, simply create a wrapper that derives from the provided base class. Ultimately we aim to improve the reproducibility of local motion planning algorithms and encourage standardized open-source comparison.
