Sampling-Based Optimal(SBO) path planning has been mainly used for robotic arm manipulation tasks. Several research works have been carried out in order to evaluate performances of various SBO planners for arm manipulation. However, not much of work is available that highlights performances of SBO planners in context of mobile robot navigation in outdoor 3D environments. This paper evaluates performances of major SBO planners in Open Motion Planning Library(OMPL) for that purpose. Due to large number of existing SBO planners, experimenting and selecting a proper planner for a planning problem can be burdensome and ambiguous. SBO planner's probabilistic nature can also add a bias to this procedure. To address this, we evaluate performances of all available SBO planners in OMPL with a randomized planning problem generation method iteratively. Evaluations are done in various state spaces suiting for different differential constraints of mobile robots. The planning setups are focused for navigation of mobile robots in outdoor environments. The outdoor environment representation is done with prebuilt OctoMaps, collision checks are performed between a 3D box representing robot body and OctoMap for validation of sampled states. Several evaluation metrics such as resulting path's length, smoothness and status of acquired final solutions are selected. According to selected metrics, performances from different SBO planners are presented comparatively. Experimental results shows the significance of parallel computing towards quicker convergence rates for optimal solutions. Several SBO methods that takes advantage of parallel computing produced better results consistently in all state spaces for different planning inquiries.
翻译:以抽样为基础的最佳方法(SBO)路径规划主要用于机器人手臂操纵任务。已经开展了一些研究工作,以评价各SBO规划者进行手臂操纵的绩效。然而,目前没有多少工作能够突出SBO规划者在户外3D环境中移动机器人导航方面的业绩。本文评估了开放运动规划图书馆(OMPL)中主要SBO规划者为此在开放运动规划图书馆(OMPL)的绩效。由于现有的SBO规划者人数众多,试验和选择一个适当的平行空间规划者处理规划问题可能会负担过重和模糊不清。SBO规划员的概率性质也可以为这一程序增加偏差。为了解决这个问题,我们评估了OMPL所有可用的SBO规划者的业绩,同时采用随机化的规划问题生成方法。 在不同州里进行了评估,适合移动机器人的不同限制。 规划组侧重于在室外环境中对移动机器人的导航。 室外环境代表与事先安装的OchoMaps进行对比,在代表机器人的3D优势调查中进行若干次碰撞检查,在代表机器人机体间进行更精确的比重的比重的比重评价,并测试结果为SBOBOBA的精选定的标状况。 。在S的标定的标定的标状态上进行。