移动机器人避障与轨迹规划

发布时间：2018-06-27 18:29

本文选题：路径规划 + 轨迹规划　；参考：《浙江大学》2017年硕士论文

【摘要】：导航规划作为移动机器人的核心算法,为机器人提供了基于感知移动作业的能力,是学术界和工业界的热点问题。机器人的导航规划一般分为构建地图、自定位、路径规划和轨迹规划四个部分。本文主要研究其中的路径规划和轨迹规划部分。本文内容和研究成果如下:1.实现了基于泰森多边形(GVD,GeneralizedVoronoiDiagram)的栅格地图与混合A*算法的全局路径规划改进算法。该方法与传统的全局路径规划算法相比,考虑了机器人的几何约束,即最小转弯半径,同时引入Reeds-Shepp最优轨迹加速算法速度用以跳过大量开阔的搜索空间,并用梯度下降法优化了混合A*规划出来的路径,使最后的规划路径更加平滑合理。2.提出了一种基于图优化的轨迹规划方法TEB(TimedElasticBand)的改进算法。本文用混合A*算法得到的全局路径作为TEB算法的初值进行优化,且在计算下发速度时变换了思路,采用轨迹跟踪的算法跟踪TEB优化后的轨迹替换原来的速度计算。此外,相比TEB算法最大速度与最大角速度的约束,在原有算法的基础上进一步增加了速度与角速度的联合约束,使整个算法更加合理。3.提出了一种采用PD控制器和非线性模型预测控制(NMPC,Nonlinear Model Predictive Control)优化的路径追踪方法。其中基于NMPC的轨迹跟踪方法考虑了机器人本身的模型信息,有效提高了轨迹跟踪的精度,轨迹规划的控制周期能时刻保持在40ms以内。
[Abstract]:As the core algorithm of mobile robots, navigation planning provides robots with the ability to perceive mobile operations, which is a hot issue in academia and industry. Robot navigation planning is generally divided into four parts: building map, self-positioning, path planning and trajectory planning. This paper mainly studies the path planning and trajectory planning. The contents and results of this paper are as follows: 1. An improved algorithm of global path planning based on GVDX Generalized Voron Diagram and hybrid A * algorithm is implemented. Compared with the traditional global path planning algorithm, this method takes into account the geometric constraints of the robot, that is, the minimum turning radius, and introduces the Reeds-Shepp optimal trajectory acceleration algorithm to skip a large number of open search spaces. The gradient descent method is used to optimize the path of mixed A * programming to make the final planning path more smooth and reasonable. 2. An improved trajectory planning method TEB (timed Elastic Band) based on graph optimization is proposed. In this paper, the global path obtained by the hybrid A * algorithm is used as the initial value of the TEB algorithm, and the train of thought is changed in the calculation of the down firing speed. The trajectory tracking algorithm is used to track the TEB's optimized trajectory instead of the original speed calculation. In addition, compared with the constraint of the maximum velocity and the maximum angular velocity of the TEB algorithm, the combined constraint of the velocity and the angular velocity is added further on the basis of the original algorithm, which makes the whole algorithm more reasonable. 3. A path tracing method based on PD controller and nonlinear model predictive control is proposed. The trajectory tracking method based on NMPC takes into account the model information of the robot itself and effectively improves the accuracy of trajectory tracking. The control cycle of trajectory planning can be kept within 40ms at all times.
【学位授予单位】：浙江大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TP242

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