非完整移动小车的运动学和动力学建模

非完整移动小车的运动学和动力学建模(任务书,开题报告,论文说明书16000字)
摘要
随着计算机计算速度的日益提高，智能算法的完善和不断改进提高，智能化产品的应用范围得到极大的扩展，其中智能驾驶是个应用前进广阔的领域，是现在研究的热点。无人驾驶车辆是一个利用计算机，使用传感器，通信等技术实现驾驶环境的感知测量，采用先进智能算法实现无人驾驶过程中的决策规划的新兴技术产品，彻底颠覆了传统驾驶方式。其中智能车辆的自动泊车问题是一个重要的研究难点，泊车过程是一个求解车辆在复杂环境中，即在多约束的情况下，寻找一条合适的路径的过程，无碰撞稳定地到达合适位置点的过程。因此针对智能小车这个非完整约束系统，设计合适的算法，实现轨迹规划；建立合理的控制器实现轨迹的跟踪，使得小车稳定的安全地泊车入库。
本文中分析泊车环境，将复杂的环境约束转换为数学语言描述，并建立小车模型，分析其几何约束，建立运动学关系，通过分析以上的约束条件，论文中设计的势场算法和优化算法两种方法实现轨迹规划。具体的研究内容包括以下几个方面：
1）采用数学语言对环境约束进行抽象化，建立小车的模型，分析几何关系，运动学约束，得到转角，车体与位姿关系。 [来源：http://think58.com]
2）针对小车模型，提出一种改进的人工势场法和一个基于多项式拟合的算法，实现轨迹规划，同时满足小车运动学约束；并且证明改进的人工势场能够有效的满足约束条件，最后进行优化光滑处理，得到光滑的轨迹线。
3）对轨迹进行离散化，设计PID算法，调节比例积分微分各个环节的参数，实现轨迹跟踪，满足小车寻迹过程中的位置误差和航向误差，最后进行仿真证明设计的PID算法控制的有效性。
综合上述的研究内容，设计和实现了基于改进的人工势场法的轨迹规划和PID控制器的设计，并且利用上述算法完成了小车平行泊车和垂直泊车两种的仿真实验。结果表明，本文中设计的规划算法和控制算法稳定安全地实现了泊车过程，从而证明了本文中提出的改进势场法的有效性和控制过程的合理性。
关键词：非完整约束，改进人工势场；多项式拟合；PID控制；泊车

Abstract
With the increasing computational speed of computers, the improvement and improvement of intelligent algorithms, the range of application of intelligent products has been greatly expanded, and smart driving is an area where applications are moving forward. It is a research hotspot. The driverless vehicle is an emerging technology product that uses computer, sensor, communication and other technologies to realize the perception measurement of the driving environment, uses advanced intelligent algorithms to realize decision planning in the driverless process, and completely overturns the traditional driving method. Among them, the automatic parking problem of intelligent vehicles is an important research difficulty. The parking process is a process to solve the vehicle in a complex environment, that is, in the case of multiple constraints, to find a suitable path, to reach the appropriate location without collision and stability. Point process. Therefore, for the non-holonomic restraint system of smart car, an appropriate algorithm is designed to realize trajectory planning; a reasonable controller is implemented to track the trajectory so that the car can be parked safely and securely.

[资料来源：http://THINK58.com]

This article analyzes the parking environment, converts the complex environmental constraints into mathematical language descriptions, builds a trolley model, analyzes its geometric constraints, establishes kinematic relationships, and analyzes the above constraints to design potential field algorithms and optimization algorithms. Two ways to achieve trajectory planning. The specific research includes the following aspects:
1) Using mathematical language to abstract the environmental constraints, establish the model of the car, analyze the geometric relations, kinematic constraints, get the corner, the relationship between the body and pose.
2) For the trolley model, an improved artificial potential field method and a polynomial fitting algorithm are proposed to realize trajectory planning and meet the constraints of the kinematics of the vehicle at the same time. It is also proved that the improved artificial potential field can effectively satisfy the constraint conditions. Optimize smoothing to get a smooth trajectory. [资料来源：THINK58.com]
3) Discretize the trajectory, design the PID algorithm, adjust the parameters of each part of the proportional integral differential, realize trajectory tracking, meet the position error and heading error in the tracking process of the car, and finally simulate to prove the effectiveness of the PID control algorithm. .

Based on the above research contents, the trajectory planning and PID controller design based on the improved artificial potential field method are designed and implemented. And the above simulations are used to complete the parallel parking simulation and vertical parking simulation. The results show that the planning algorithm and control algorithm designed in this paper achieve a stable and secure parking process, which proves the effectiveness of the improved potential field method proposed in this paper and the rationality of the control process.

Keywords: Non-holonomic constraints, Improved artificial potential field; Polynomial fitting; PID control; Parking

[来源：http://www.think58.com]

目录
第1章    绪论    1
1.1 研究背景    1
1.2 非完整约束小车的发展现状    2
1.2.1 轨迹规划    5
1.2.2.轨迹跟踪控制    6
1.3 研究本课题的意义    7
1.4 研究的主要内容    7
第2章    非完整约束小车建模及约束分析    8
2.1 非完整约束小车介绍    8
2.2非完整约束小车模型    10
2.3非完整约束小车约束条件分析    12
第3章    轨迹规划算法研究    14
3.1 基于改进的人工势场法    14
3.1.1 改进人工势场    14
3.1.2 仿真测试    16
3.2 基于多项式拟合进行轨迹规划及仿真    19
3.2.1 基于多项式算法规划    19
3.2.2 仿真及测试    20
3.3 本章小结    23
第4章    基于PID轨迹跟踪控制算法    25 [来源：http://www.think58.com]
4.1 PID控制的基本原理    25
4.2 小车的运动学模型    25
4.3 PID控制模型及跟踪策略    28
4.4 PID控制模拟仿真    31
4.5 本章小结    34
第5章    总结和展望    35
5.1 总结    35
5.2 展望    35
参考文献    37
附录    40
致谢    46