Примитивы движения робота в задаче планирования траектории с кинематическими ограничениями

Vladislav Golovin, Konstantin Yakovlev
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Abstract

Automatic trajectory planning is an urgent scientific and technical problem, whose solutions are in demand in many fields: unmanned transportation, robotic logistics, social robotics, etc. Often, when planning a trajectory, it is necessary to consider the fact that the agent (robot, unmanned car, etc.) cannot arbitrarily change its orientation while moving, in other words, it is necessary to consider kinematic constraints when planning. One widespread approach to solving this problem is the approach that relies on the construction of a trajectory from prepared parts, motion primitives, each of which satisfies kinematic constraints. Often, the emphasis in the development of methods implementing this approach is on reducing the combinations of choices in planning (heuristic search), with the set of available primitives itself being regarded as externally defined. In this paper, on the contrary, we aim to investigate and analyze the effect of different available motion primitives on the quality of solving the planning problem with a fixed search algorithm. Specifically, we consider 3 different sets of motion primitives for a wheeled robot with differential drive. As a search algorithm, the A* algorithm well known in artificial intelligence and robotics is used. The solution quality is evaluated by 6 metrics, including planning time, length and curvature of the resulting trajectory. Based on the study, conclusions are made about the factors that have the strongest influence on the planning result, and recommendations are given on the construction of motion primitives, the use of which allows to achieve a balance between the speed of the planning algorithm and the quality of the trajectories found.
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机器人在运动限制轨道规划任务中的原始动作
自动轨迹规划是一个亟待解决的科学技术问题,在无人运输、机器人物流、社交机器人等领域都有解决方案。通常,在规划轨迹时,需要考虑agent(机器人、无人车等)在运动时不能任意改变其方向,也就是说,在规划时需要考虑运动学约束。解决这个问题的一种广泛的方法是依赖于从准备好的部件、运动原语构建轨迹的方法,每个原语都满足运动学约束。通常,实现这种方法的方法开发的重点是减少规划中的选择组合(启发式搜索),可用的原语集本身被视为外部定义的。相反,在本文中,我们的目的是研究和分析不同可用的运动原语对固定搜索算法求解规划问题质量的影响。具体来说,我们考虑了带差动驱动的轮式机器人的3组不同的运动原语。作为一种搜索算法,使用了人工智能和机器人技术中众所周知的a *算法。解决方案的质量由6个指标来评估,包括规划时间、长度和结果轨迹的曲率。在此基础上,总结了对规划结果影响最大的因素,并对运动原语的构造提出了建议,使用运动原语可以在规划算法的速度和找到的轨迹质量之间取得平衡。
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