In general, optimal motion planning can be performed both locally and globally. In such a planning, the choice in favour of either local or global planning technique mainly depends on whether the environmental conditions are dynamic or static. Hence, the most adequate choice is to use local planning or local planning alongside global planning. When designing optimal motion planning both local and global, the key metrics to bear in mind are execution time, asymptotic optimality, and quick reaction to dynamic obstacles. Such planning approaches can address the aforesaid target metrics more efficiently compared to other approaches such as path planning followed by smoothing. Thus, the foremost objective of this study is to analyse related literature in order to understand how the motion planning, especially trajectory planning, problem is formulated, when being applied for generating optimal trajectories in real-time for Multirotor Aerial Vehicles (MAVs), impacts the listed metrics. As a result of the research, the trajectory planning problem was broken down into a set of subproblems, and the lists of methods for addressing each of the problems were identified and described in detail. Subsequently, the most prominent results from 2010 to 2022 were summarized and presented in the form of a timeline.
翻译:一般而言,最佳运动规划可以在当地和全球范围内进行,在这种规划中,有利于地方或全球规划技术的选择主要取决于环境条件是动态的还是静态的。因此,最适当的选择是利用地方规划或与全球规划一起进行地方规划或地方规划。在设计最佳运动规划时,需要考虑的关键衡量标准是执行时间、无症状的最佳性以及对动态障碍的快速反应。这种规划方法可以比其他方法(例如路标规划,然后是顺利进行)更高效地处理上述目标指标。因此,本研究的首要目标是分析相关文献,以便了解如何在实时为多色飞行器创造最佳轨迹时,特别是在轨迹规划方面,如何提出问题。由于研究的结果,轨迹规划问题被细分为一套子问题,解决每个问题的方法清单也得到了确定和详细描述。随后,以时间表的形式总结并介绍了2010年至2022年最突出的结果。