移动机器人导航中的轨迹跟踪与群集运动控制研究
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摘要
随着科学技术的发展，移动机器人研究受到控制和人工智能等领域学者的广泛关注。目前，现代移动机器人进入了一个崭新的研究阶段，在工业、农业、国防、服务和科学研究等方面得到了广泛应用，以代替人类完成很多繁重或恶劣条件下无法胜任的工作。本文的研究工作紧密围绕轮式移动机器人导航中的轨迹跟踪和群集运动控制两大关键技术展开。在第一部分研究内容中，重点研究约束非理想情况下轮式移动机器人的数学模型和轨迹跟踪控制，分别针对运动学和动力学模型提出了新的轨迹跟踪控制算法，以提高移动机器人的轨迹跟踪精度。在第二部分研究工作中，为解决未知环境下移动机器人的自主导航和群集运动控制问题，将虚拟子目标和禁忌搜索算法引入到机器人路径规划技术中，提出相应的自主导航和群集运动控制算法，对改善导航效率和推动机器人由半自主式向智能型发展有十分重要的意义。论文的主要研究工作和成果如下：
1、建立了约束非理想情况下双轮差分驱动轮式移动机器人的运动学模型、动力学模型和驱动模型，为移动机器人轨迹跟踪控制、未知环境下自主导航和群集运动控制研究奠定了基础。
2、通过对约束非理想情况下轮式移动机器人轨迹跟踪问题的研究，得到了以两独立驱动轮角速度为控制输入的机器人运动学模型。针对模型中存在的未知参数，采用反演设计和滑模控制的方法给出了自适应滑模轨迹跟踪控制律，并利用Lyapunov稳定性理论证明了轨迹跟踪误差的全局一致渐近稳定性。
3、针对动力学模型描述的约束非理想轮式移动机器人系统，提出了一种全局渐近稳定的自适应积分滑模控制律。该方法首先借助运动学模型设计了中间辅助控制变量，然后利用反演技术和积分滑模控制的思想设计了自适应积分滑模控制律，可实现移动机器人轨迹跟踪的要求。最后通过仿真算例验证了控制律的有效性和正确性。
4、为提高轨迹跟踪性能，在轮式移动机器人动力学模型的基础上进一步考虑驱动模型的影响，在以电机电压为控制输入、存在不确定参数和外界干扰时，设计了一种自适应轨迹跟踪控制律，以满足移动机器人的高精度轨迹跟踪要求。
5、针对未知环境下纯粹的反应式导航算法缺少“预见性”的缺点，设计了一种基于虚拟子目标的轮式移动机器人主动寻径导航算法。该算法利用禁忌搜索算法识别感知域内的优化子目标，并采用模糊控制的方法对子目标进行跟踪，以逐步渐进的方式实现无碰路径优化并到达最终目标。仿真和实验结果验证了所设计导航算法的有效性和正确性。
6、针对群集运动系统在非规则障碍物的未知环境中运行时容易陷入局部极小的问题，将个体扩展为具有记忆能力的智能个体，提出了一类基于虚拟子目标的Leader-Follower智能群体避障和群集运动控制策略，并通过动力学分析和虚拟力分解使基于智能体的群集控制律转化到多移动机器人系统，实现了多移动机器人在未知障碍物环境下的群集运动控制。
With the development of science and technology, autonomous mobile robotshave attracted many researchers from the control and artificial intelligence community.Recently, modern mobile robots have entered a new research stage, and have beenapplied to many fields, such as industry, agriculture, national defence, service,scientific research and so on. The intelligent mobile robots are capable of performingsome disgusting, heavy or harsh tasks historically assigned to human beings. In thisdissertation, we mainly concentrate on two main control techniques of trajectorytracking and flocking motion for the autonomous navigation of wheeled mobile robots.In the first part, we focus on the modeling and trajectory tracking control of wheeledmobile robot with non-ideal constraint. Moreover, the novel trajectory trackingcontrol algorithms based on kinematic and dynamic model respectively are present toimprove the accuracy of trajectory tracking for the wheeled mobile robot. In thesecond part, we investigate the problem of autonoumous navigation and flockingmotion control in unknown condition. In order to explore new approaches ofautonomous navigation and promote the intelligence of half an autonomous mobilerobot, we introduce the virtual sub-goal and tabu search algorithm to path planningtechniques of mobile robot, and propose the corresponding algorithms of autonomousnavigation and flocking motion control for mobile robots. The main research workand contributions of the dissertation are summarized as follows:
1. For wheeled mobile robot with two independent driven wheel angularvelocities and non-ideal constraint, the kinematic model, dynamic model and drivenmodel of mobile robot are established for the research purposes and foundation oftrajectory tracking control, autonomous navigation and flocking motion control inunknown environment.
2. A robot kinematic model with two independent driven wheel angular velocitiesas control inputs is obtained by analyzing the trajectory tracking problem for wheeledmobile robot whose mass centers are not coincidental with the geometrical centers.For the unknown wheel radius and the distance between the two driving wheels, anadaptive sliding-mode tracking control law is proposed by employing backsteppingmethod and sliding-mode control. The global asymptotically stability of the closedloop system is guaranteed by Lyapunov stability theory.
3. In order to solve the trajectory tracking problem for the dynamic model of mobile robot with non-ideal constraint, an adaptive integral sliding-mode control lawis proposed in this chapter. A virtual control variable is firstly introduced according tothe kinematic model. Then an adaptive sliding-mode controller is designed byemploying backstepping technique and intergral sliding-mode control algorithm,which can realize the trajectory tracking requirements with strong robustness. Finally,the effectiveness and correctiveness of the proposed control law are demonstrated bysimulation examples.
4. On the basis of the dynamic model for wheeled mobile robot, the driven motordynamics is taken into account further to improve the performance of trajectorytracking. By employing the voltage of motor as control input, an adaptive trajectorytracking control law for mobile robot system with uncertain inertia parameters,uncertain structure parameters and external disturbance is presented for this case toensure robustness to the uncertainty of model parameters. The proposed control lawcan guarantee that the mobile robot will track the desired trajectory accurately.
5. Due to the lack of predictability by using reactive navigation algorithm inunknown condition, an active routing navigation algorithm based on sub-goal isdesigned for mobile robot. By analyzing the data collected by laser radar and usingtabu search algorithm, the above algorithm can identify the optimized sub-goal. Thenthe mobile robot can realize the free-obstacle and optimization path based on fuzzylogic control method by gradual way. Simulation and experiment results show that theproposed algorithm is correct and effective.
6. In order to solve the local minimum problem encounted within variousflocking systems in unexpected and irregular obstacle environment, the virtualsub-goal based flocking motion and obstacle avoidance control strategy is proposedby giving individual agents some limited memories. By considering the dynamicanalysis and virtual force decomposition, an overall control algorithm of multi-robotsgroup is devised by transforming the agent-based flocking control strategy. Themulti-robots group can be more effieient to achieve flocking motion in obstacleenvironment.
1、建立了约束非理想情况下双轮差分驱动轮式移动机器人的运动学模型、动力学模型和驱动模型，为移动机器人轨迹跟踪控制、未知环境下自主导航和群集运动控制研究奠定了基础。
2、通过对约束非理想情况下轮式移动机器人轨迹跟踪问题的研究，得到了以两独立驱动轮角速度为控制输入的机器人运动学模型。针对模型中存在的未知参数，采用反演设计和滑模控制的方法给出了自适应滑模轨迹跟踪控制律，并利用Lyapunov稳定性理论证明了轨迹跟踪误差的全局一致渐近稳定性。
3、针对动力学模型描述的约束非理想轮式移动机器人系统，提出了一种全局渐近稳定的自适应积分滑模控制律。该方法首先借助运动学模型设计了中间辅助控制变量，然后利用反演技术和积分滑模控制的思想设计了自适应积分滑模控制律，可实现移动机器人轨迹跟踪的要求。最后通过仿真算例验证了控制律的有效性和正确性。
4、为提高轨迹跟踪性能，在轮式移动机器人动力学模型的基础上进一步考虑驱动模型的影响，在以电机电压为控制输入、存在不确定参数和外界干扰时，设计了一种自适应轨迹跟踪控制律，以满足移动机器人的高精度轨迹跟踪要求。
5、针对未知环境下纯粹的反应式导航算法缺少“预见性”的缺点，设计了一种基于虚拟子目标的轮式移动机器人主动寻径导航算法。该算法利用禁忌搜索算法识别感知域内的优化子目标，并采用模糊控制的方法对子目标进行跟踪，以逐步渐进的方式实现无碰路径优化并到达最终目标。仿真和实验结果验证了所设计导航算法的有效性和正确性。
6、针对群集运动系统在非规则障碍物的未知环境中运行时容易陷入局部极小的问题，将个体扩展为具有记忆能力的智能个体，提出了一类基于虚拟子目标的Leader-Follower智能群体避障和群集运动控制策略，并通过动力学分析和虚拟力分解使基于智能体的群集控制律转化到多移动机器人系统，实现了多移动机器人在未知障碍物环境下的群集运动控制。
With the development of science and technology, autonomous mobile robotshave attracted many researchers from the control and artificial intelligence community.Recently, modern mobile robots have entered a new research stage, and have beenapplied to many fields, such as industry, agriculture, national defence, service,scientific research and so on. The intelligent mobile robots are capable of performingsome disgusting, heavy or harsh tasks historically assigned to human beings. In thisdissertation, we mainly concentrate on two main control techniques of trajectorytracking and flocking motion for the autonomous navigation of wheeled mobile robots.In the first part, we focus on the modeling and trajectory tracking control of wheeledmobile robot with non-ideal constraint. Moreover, the novel trajectory trackingcontrol algorithms based on kinematic and dynamic model respectively are present toimprove the accuracy of trajectory tracking for the wheeled mobile robot. In thesecond part, we investigate the problem of autonoumous navigation and flockingmotion control in unknown condition. In order to explore new approaches ofautonomous navigation and promote the intelligence of half an autonomous mobilerobot, we introduce the virtual sub-goal and tabu search algorithm to path planningtechniques of mobile robot, and propose the corresponding algorithms of autonomousnavigation and flocking motion control for mobile robots. The main research workand contributions of the dissertation are summarized as follows:
1. For wheeled mobile robot with two independent driven wheel angularvelocities and non-ideal constraint, the kinematic model, dynamic model and drivenmodel of mobile robot are established for the research purposes and foundation oftrajectory tracking control, autonomous navigation and flocking motion control inunknown environment.
2. A robot kinematic model with two independent driven wheel angular velocitiesas control inputs is obtained by analyzing the trajectory tracking problem for wheeledmobile robot whose mass centers are not coincidental with the geometrical centers.For the unknown wheel radius and the distance between the two driving wheels, anadaptive sliding-mode tracking control law is proposed by employing backsteppingmethod and sliding-mode control. The global asymptotically stability of the closedloop system is guaranteed by Lyapunov stability theory.
3. In order to solve the trajectory tracking problem for the dynamic model of mobile robot with non-ideal constraint, an adaptive integral sliding-mode control lawis proposed in this chapter. A virtual control variable is firstly introduced according tothe kinematic model. Then an adaptive sliding-mode controller is designed byemploying backstepping technique and intergral sliding-mode control algorithm,which can realize the trajectory tracking requirements with strong robustness. Finally,the effectiveness and correctiveness of the proposed control law are demonstrated bysimulation examples.
4. On the basis of the dynamic model for wheeled mobile robot, the driven motordynamics is taken into account further to improve the performance of trajectorytracking. By employing the voltage of motor as control input, an adaptive trajectorytracking control law for mobile robot system with uncertain inertia parameters,uncertain structure parameters and external disturbance is presented for this case toensure robustness to the uncertainty of model parameters. The proposed control lawcan guarantee that the mobile robot will track the desired trajectory accurately.
5. Due to the lack of predictability by using reactive navigation algorithm inunknown condition, an active routing navigation algorithm based on sub-goal isdesigned for mobile robot. By analyzing the data collected by laser radar and usingtabu search algorithm, the above algorithm can identify the optimized sub-goal. Thenthe mobile robot can realize the free-obstacle and optimization path based on fuzzylogic control method by gradual way. Simulation and experiment results show that theproposed algorithm is correct and effective.
6. In order to solve the local minimum problem encounted within variousflocking systems in unexpected and irregular obstacle environment, the virtualsub-goal based flocking motion and obstacle avoidance control strategy is proposedby giving individual agents some limited memories. By considering the dynamicanalysis and virtual force decomposition, an overall control algorithm of multi-robotsgroup is devised by transforming the agent-based flocking control strategy. Themulti-robots group can be more effieient to achieve flocking motion in obstacleenvironment.
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