轮式餐厅服务机器人移动定位技术研究
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摘要
从20世纪末期以来，国内外众多学者便致力于室内环境下服务机器人的系统研究，并在理论和实际应用中取得了丰硕的研究成果。由于移动定位技术是机器人路径规划和导航的关键，因此引起了国内外学者的广泛关注，逐渐成为服务机器人领域的一个研究热点。为了提高餐厅服务机器人系统的可靠性，本文对服务机器人在餐厅环境下的移动定位技术进行了深入研究，提高了机器人的定位精度，确保餐厅服务机器人能够为顾客提供自主取菜、送菜等餐饮服务。论文从建立餐厅服务机器人系统入手，进行餐厅环境下服务机器人移动定位技术研究，主要研究工作包括如下方面：
1、基于轮式移动机构建立了轮式餐厅服务机器人系统，分析设计了机器人的机械系统和传感器系统。建立了餐厅服务机器人的运动学模型、里程计模型和机械臂的正运动学模型，通过对机械臂的正运动学模型进行仿真分析，明确了餐厅服务机器人在少自由度下完成自主取菜任务的重点、难点。针对餐厅服务机器人的传感器系统特点，建立了双目视觉路标观测模型和全局视觉传感器观测模型，为服务机器人的环境感知和移动定位技术研究奠定必要的基础。
2、为了提高餐厅服务机器人的全局定位精度，提出了一种改进的迭代扩展卡尔曼粒子滤波算法。该算法采用Levenberg-Marquardt优化方法，对迭代扩展卡尔曼滤波进行优化、修正，解决了迭代卡尔曼滤波有时收敛速度慢的问题，并减少了初始状态对滤波性能的影响；以改进迭代卡尔曼滤波的最大后验概率估计来产生粒子滤波的重要性概率密度函数，充分利用了改进算法对非线性问题的处理能力，产生更好的参考分布。采用典型非线性系统模型对粒子滤波算法进行仿真分析，验证了改进粒子算法的状态估计精度要优于其它粒子滤波算法。提出了一种基于改进迭代卡尔曼粒子滤波的机器人全局视觉定位方法，实现了机器人的全局定位，并应用到餐厅服务机器人中进行实验验证，满足了餐厅服务机器人移动导航时对定位精度和实时性要求。
3、为了提高餐厅服务机器人全局定位的准确性和可靠性，基于对多信息融合理论的深入研究和探讨，提出了集中式、分布式和联合式等三种迭代扩展卡尔曼多信息融合算法，解决了非线性环境下的多传感器信息融合问题，采用典型的非线性系统模型，对提出的多信息融合算法进行仿真分析。提出了一种基于联合迭代卡尔曼多信息融合的餐厅服务机器人定位算法，融合里程计、视觉路标和全局视觉数据，有效地提高了机器人全局定位的精度和可靠性，并进行了实际应用验证。
4、基于Mean-Shift颜色分割与SIFT特征匹配技术，提出了一种基于图像分割的区域稠密匹配算法，通过Mean-Shift分割方法对参考图像进行图像分割，由SIFT算子提取并匹配立体图像对中的SIFT特征点，根据图像分割块中SIFT特征点对的分布情况，对各个图像分割块单独进行区域匹配，获得立体图像对的较准确、稠密的区域匹配。采用标准的立体图像对，进行仿真分析，并与文献中匹配算法的视差图及标准视差图进行比较，论证了文中立体匹配算法的准确性、可靠性和稳定性。提出了一种基于双目视觉的服务机器人目标位姿精定位算法，实现服务机器人趋近目标物及机器人相对目标特征点的精定位，并应用到餐厅服务机器人中进行实验验证，餐厅服务机器人能够成功完成自主取菜任务。
本论文构建了轮式餐厅服务机器人平台，研究了机器人的运动学模型和传感器观测模型，通过对粒子滤波定位、多信息融合定位和立体图像匹配等方面的研究，为室内环境下机器人移动定位研究提供了有利参考。本文提出的服务机器人移动定位算法成功应用到餐厅服务机器人中，大量实验证明该定位算法能够有效地提高餐厅服务机器人的定位精度和可靠性，对室内环境下机器人移动定位具有参考价值。
Since the late20th century, many scholars have begun to study the servicerobots in indoor environment, and made great achievements in the theory andpractice. As the mobile positioning technology is the key of the navigation andpath planning, localization has become a hot topic and drawn greater attention.To enhance the reliability of the restaurant service robot system, the mobilepositioning technology of service robot has been profoundly studied in thispaper. And the localization accuracy has been improved to ensure that therestaurant service robot could serve and deliver dishes for the customers inrestaurant environment. Then begin with the establishment of restaurant servicerobot systems, based on it indoor mobile localization is done, those as follows.
1. A type of wheeled restaurant service robot system is established based onthe wheeled robot principle and analyze the mechanical system and sensorsystems. Establish the kinematic model and odometer model of the restaurantservice robot and the kinematic model of the manipulator. According to thesimulation of the manipulator kinematic model, define the emphasis and difficulty of the serving dishes task of the robot in less degrees of freedom.According to the characteristics of the sensor systems, establish the observationmodels of binocular and global visual sensors, and lay the necessary foundationfor environment perception and positioning techniques.
2. To enhance the positioning accuracy of the restaurant service robot, animproved iterative extended Kalman particle filter algorithm (PF-UIEKF) isproposed. The algorithm optimizes the iterative extended Kalman filter (IEKF)using the Levenberg-Marquardt method, to amend the problem that IEKF issometimes slow to convergence and resolve the impact of the initial state on thefilter effect. The algorithm uses the maximum posteriori estimates of theoptimized IEKF to generate the importance probability density function, andtakes full advantage of its handling capacity of the nonlinear problem to producethe better reference distribution. Simulate the various particle filter algorithmswith the typical nonlinear model, comparing with the simulation results of theseparticle filters, verify that the state estimation accuracy of the proposedalgorithm is much better than the other particle filters. A global visuallocalization algorithm based on PF-UIEKF is proposed to position the mobilerobot, and the algorithm is applied to restaurant service robot and experimentsverify that it meets the positioning accuracy and real-time requirements ofservice robot mobile navigation.
3. To improve the positioning accuracy and reliability of the restaurantservice robot, based on the study and discussion of multi-information fusiontheory, centralized, distributed and federal IEKF multi-information fusionalgorithms are proposed to fuse the multi-sensor information in nonlinearenvironment. Respectively simulate the proposed multi-information fusionalgorithms using the typical nonlinear model to verify their state estimationperformance. A localization method based on federal IEKF multi-informationfusion is proposed to fuse the information of odometer, visual landmark andglobal vision, and the practical application verifies that the algorithm couldeffectively improve the positioning accuracy and reliability.
4. Based on the mean-shift color segmentation and the SIFT featurematching technology, a regional dense matching algorithm is proposed. Thealgorithm does image segmentation with mean-shift method, extracts andmatches the feature points using the SIFT operator. According to whethersegmentation region contains the SIFT feature points, separately match eachimage region using the different methods to obtain the more accurate disparitymap. Simulate and analyze the proposed matching algorithm using theprofessional stereo image pairs to verify the accuracy, reliability and stability ofthe matching algorithm. A fine positioning algorithm of robot target pose basedon binocular vision is proposed to realize mobile robot moving towards the target and the precise positioning of the service robot relative to the targetfeature. The method is applied to restaurant service robot for experimentalverification and the service robot can successfully complete the self-servingdelicious task.
In this thesis, a restaurant service robot platform is developed, and thekinematic model of the robot and sensor observation model are also studied. Theaccuracy and reliability of the mobile positioning have been obviously enhancedby researching the particle filter, the multi-information fusion and the imagematching technology. And the proposed algorithms provide a favorablereference for indoor service robot localization. The proposed algorithms havebeen successfully applied in the restaurant service robot. Many practicalapplications verify that the proposed algorithms can effectively enhance thepositioning accuracy and stability of the service robot and possess a practicalreference value.
1、基于轮式移动机构建立了轮式餐厅服务机器人系统，分析设计了机器人的机械系统和传感器系统。建立了餐厅服务机器人的运动学模型、里程计模型和机械臂的正运动学模型，通过对机械臂的正运动学模型进行仿真分析，明确了餐厅服务机器人在少自由度下完成自主取菜任务的重点、难点。针对餐厅服务机器人的传感器系统特点，建立了双目视觉路标观测模型和全局视觉传感器观测模型，为服务机器人的环境感知和移动定位技术研究奠定必要的基础。
2、为了提高餐厅服务机器人的全局定位精度，提出了一种改进的迭代扩展卡尔曼粒子滤波算法。该算法采用Levenberg-Marquardt优化方法，对迭代扩展卡尔曼滤波进行优化、修正，解决了迭代卡尔曼滤波有时收敛速度慢的问题，并减少了初始状态对滤波性能的影响；以改进迭代卡尔曼滤波的最大后验概率估计来产生粒子滤波的重要性概率密度函数，充分利用了改进算法对非线性问题的处理能力，产生更好的参考分布。采用典型非线性系统模型对粒子滤波算法进行仿真分析，验证了改进粒子算法的状态估计精度要优于其它粒子滤波算法。提出了一种基于改进迭代卡尔曼粒子滤波的机器人全局视觉定位方法，实现了机器人的全局定位，并应用到餐厅服务机器人中进行实验验证，满足了餐厅服务机器人移动导航时对定位精度和实时性要求。
3、为了提高餐厅服务机器人全局定位的准确性和可靠性，基于对多信息融合理论的深入研究和探讨，提出了集中式、分布式和联合式等三种迭代扩展卡尔曼多信息融合算法，解决了非线性环境下的多传感器信息融合问题，采用典型的非线性系统模型，对提出的多信息融合算法进行仿真分析。提出了一种基于联合迭代卡尔曼多信息融合的餐厅服务机器人定位算法，融合里程计、视觉路标和全局视觉数据，有效地提高了机器人全局定位的精度和可靠性，并进行了实际应用验证。
4、基于Mean-Shift颜色分割与SIFT特征匹配技术，提出了一种基于图像分割的区域稠密匹配算法，通过Mean-Shift分割方法对参考图像进行图像分割，由SIFT算子提取并匹配立体图像对中的SIFT特征点，根据图像分割块中SIFT特征点对的分布情况，对各个图像分割块单独进行区域匹配，获得立体图像对的较准确、稠密的区域匹配。采用标准的立体图像对，进行仿真分析，并与文献中匹配算法的视差图及标准视差图进行比较，论证了文中立体匹配算法的准确性、可靠性和稳定性。提出了一种基于双目视觉的服务机器人目标位姿精定位算法，实现服务机器人趋近目标物及机器人相对目标特征点的精定位，并应用到餐厅服务机器人中进行实验验证，餐厅服务机器人能够成功完成自主取菜任务。
本论文构建了轮式餐厅服务机器人平台，研究了机器人的运动学模型和传感器观测模型，通过对粒子滤波定位、多信息融合定位和立体图像匹配等方面的研究，为室内环境下机器人移动定位研究提供了有利参考。本文提出的服务机器人移动定位算法成功应用到餐厅服务机器人中，大量实验证明该定位算法能够有效地提高餐厅服务机器人的定位精度和可靠性，对室内环境下机器人移动定位具有参考价值。
Since the late20th century, many scholars have begun to study the servicerobots in indoor environment, and made great achievements in the theory andpractice. As the mobile positioning technology is the key of the navigation andpath planning, localization has become a hot topic and drawn greater attention.To enhance the reliability of the restaurant service robot system, the mobilepositioning technology of service robot has been profoundly studied in thispaper. And the localization accuracy has been improved to ensure that therestaurant service robot could serve and deliver dishes for the customers inrestaurant environment. Then begin with the establishment of restaurant servicerobot systems, based on it indoor mobile localization is done, those as follows.
1. A type of wheeled restaurant service robot system is established based onthe wheeled robot principle and analyze the mechanical system and sensorsystems. Establish the kinematic model and odometer model of the restaurantservice robot and the kinematic model of the manipulator. According to thesimulation of the manipulator kinematic model, define the emphasis and difficulty of the serving dishes task of the robot in less degrees of freedom.According to the characteristics of the sensor systems, establish the observationmodels of binocular and global visual sensors, and lay the necessary foundationfor environment perception and positioning techniques.
2. To enhance the positioning accuracy of the restaurant service robot, animproved iterative extended Kalman particle filter algorithm (PF-UIEKF) isproposed. The algorithm optimizes the iterative extended Kalman filter (IEKF)using the Levenberg-Marquardt method, to amend the problem that IEKF issometimes slow to convergence and resolve the impact of the initial state on thefilter effect. The algorithm uses the maximum posteriori estimates of theoptimized IEKF to generate the importance probability density function, andtakes full advantage of its handling capacity of the nonlinear problem to producethe better reference distribution. Simulate the various particle filter algorithmswith the typical nonlinear model, comparing with the simulation results of theseparticle filters, verify that the state estimation accuracy of the proposedalgorithm is much better than the other particle filters. A global visuallocalization algorithm based on PF-UIEKF is proposed to position the mobilerobot, and the algorithm is applied to restaurant service robot and experimentsverify that it meets the positioning accuracy and real-time requirements ofservice robot mobile navigation.
3. To improve the positioning accuracy and reliability of the restaurantservice robot, based on the study and discussion of multi-information fusiontheory, centralized, distributed and federal IEKF multi-information fusionalgorithms are proposed to fuse the multi-sensor information in nonlinearenvironment. Respectively simulate the proposed multi-information fusionalgorithms using the typical nonlinear model to verify their state estimationperformance. A localization method based on federal IEKF multi-informationfusion is proposed to fuse the information of odometer, visual landmark andglobal vision, and the practical application verifies that the algorithm couldeffectively improve the positioning accuracy and reliability.
4. Based on the mean-shift color segmentation and the SIFT featurematching technology, a regional dense matching algorithm is proposed. Thealgorithm does image segmentation with mean-shift method, extracts andmatches the feature points using the SIFT operator. According to whethersegmentation region contains the SIFT feature points, separately match eachimage region using the different methods to obtain the more accurate disparitymap. Simulate and analyze the proposed matching algorithm using theprofessional stereo image pairs to verify the accuracy, reliability and stability ofthe matching algorithm. A fine positioning algorithm of robot target pose basedon binocular vision is proposed to realize mobile robot moving towards the target and the precise positioning of the service robot relative to the targetfeature. The method is applied to restaurant service robot for experimentalverification and the service robot can successfully complete the self-servingdelicious task.
In this thesis, a restaurant service robot platform is developed, and thekinematic model of the robot and sensor observation model are also studied. Theaccuracy and reliability of the mobile positioning have been obviously enhancedby researching the particle filter, the multi-information fusion and the imagematching technology. And the proposed algorithms provide a favorablereference for indoor service robot localization. The proposed algorithms havebeen successfully applied in the restaurant service robot. Many practicalapplications verify that the proposed algorithms can effectively enhance thepositioning accuracy and stability of the service robot and possess a practicalreference value.
引文
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