煤矿井下搜救探测机器人的路径规划及轨迹跟踪控制研究
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摘要
我国是世界上最大的煤炭生产国和消费国。然而,由于矿井自然条件差,高瓦斯矿井多,加上技术和管理等诸多方面不到位,以及近年来国家对煤炭资源需求量的不断增长,使得煤矿开采中瓦斯爆炸、涌水、着火等事故频繁发生,由此造成重大的人员伤亡事故和不良的社会影响,严重制约着煤炭工业的健康发展。因此,研发煤矿井下搜救探测机器人是煤矿井下发生瓦斯爆炸事故后进行抢险救援的前提手段和必要工具,它能够在矿难原因和现场情况不明的情况下,替代或部分替代救援人员进入灾害现场实施环境探测和搜救任务,同时将信息实时地传输到救援指挥中心,为救援决策提供科学依据,便于快速、准确地制定救援方案。因此,对煤矿安全生产、减少国家和人民生命财产的损失具有十分重要的意义。
本文以煤矿井下搜救探测机器人为研究对象,在对其运动装置进行设计分析的基础上,围绕移动机器人自主导航中的两项关键技术——路径规划与轨迹跟踪控制问题进行了深入的研究。首先对自主移动机器人研究中的关键技术进行了全面、系统的总结,重点对其中路径规划和轨迹跟踪控制的研究内容、存在问题及发展趋势等进行了综述,归纳总结了各种算法的性能差异,并以此为基础展开进一步的研究与探讨,主要研究内容包括以下几个方面：
提出了一种针对煤矿井下特殊环境的运动装置设计方案。对煤矿井下搜救探测机器人的运动系统、通行能力和结构特点进行了重新设计及进一步改进,并在此基础上,利用地面力学理论,参考履带车辆的运动学和动力学原理,针对煤矿井下搜救探测机器人采用差动转向的特点,建立了机器人的运动学和动力学模型,为后续的煤矿井下搜救探测机器人轨迹跟踪等控制问题的研究奠定了基础。
针对煤矿井下非结构化环境的不确定环境特征,设计了上下位机的分级控制系统,提出了一种分层协作规划与控制的体系结构。考虑到煤矿井下搜救探测机器人特定的应用环境及要求,设计了一个主要由决策系统(包括上位机监控模块、下位机控制模块、传感检测模块等)、数据通信系统和运动控制系统等组成的控制系统。并在分析当前出现的机器人各种体系结构的基础上,提出了一种从上到下依次分为决策层、慎思层和控制层的分层协作规划与控制的体系结构,能够满足机器人在未知环境下导航任务的复杂性与不确定性的要求。
结合目前具有代表性的遗传算法、蚁群算法这两种优化算法各自的特点,分别对其进行了改进。首先,设计了一种改进的遗传算法,充分考虑到井下环境地形的高低变化,采用栅格法在三维空间中对机器人工作环境进行建模,并根据路径长度最短且能耗最少的评价指标设计了适应度函数。按照可变长度的染色体编码方式及随机指导式搜索策略来生成初始种群,保证初始阶段无障碍路径的产生,同时针对传统遗传算法中存在的“早熟现象”和“收敛速度慢”的问题,将交叉算子和变异算子进行优化设计,从而使整个规划过程变得简单而有效。其次,本文还在最大—最小蚂蚁系统(MMAS)的基础上,提出了一种改进的蚁群算法,对其启发函数、路径选择规则及信息素更新方式等进行改进,加快了算法收敛速度,改善了路径规划的性能。最后通过实验对改进算法的性能进行了验证。
提出了一种用于实现机器人轨迹跟踪的模糊自适应控制器的设计方法。首先利用Lyapunov直接法设计出机器人轨迹跟踪控制系统的控制器,对机器人以期望运动速度从当前位置运动到目标点的过程进行控制,并在参考线速度不为零时,利用Barbalat引理对系统的全局一致渐近稳定性进行了证明。另外,在此基础上设计了一种模糊自适应控制器,解决了模糊多变量控制系统中规则数随系统变量数呈指数增长的问题,提高了控制器效率,且使模糊控制逻辑变得清晰明了。实验结果证明,本文设计的这两种轨迹跟踪控制器,对于不同初始误差、不同类型的参考速度都具有很好的跟踪效果。
China is the largest country of the coal production and consumption in the world. However, because of poor conditions of the coal mining system, large number of highly-gas mine and lack of effective techniques and management, especially continuous increasing demand for the coal, accidents such as gas explosion, water inflow and ignition have happened frequently in recent years. Heavy casualties and negative social effects have made healthy development of the coal industry impossible. Therefore it is premise and necessary to develop the coal mine detecting and rescuing robot. Under the circumstance the causes and field conditions of the coal mine accidents were unknown, it could substitute the rescue staff to enter the accident area for implementation of detecting and rescuing, and information can be transferred real-timely to the rescue command center simultaneously. It can provide scientific basis for the rescue decision, and the rescue plan can be made as rapidly and accurately as possible. Therefore it has critical significance for safety production in coal mine and can reduce loss of the public property and lives.
This dissertation focuses on the coal mine detecting and rescuing robot as research object, key techniques in robot autonomous navigation—path planning and trajectory tracking based on the design and analysis of its movement device were thoroughly and deeply studied. At first, the key techniques in autonomous mobile robot were summarized comprehensively and systematically, especially the research contents, existing problems and development trend of path planning and trajectory tracking were reviewed, performance differences in various algorithms were summarized and further research was developed. The main research contents included are as follows:
A kind of movement device aiming at special environment of the coal mine was proposed. The motion system, crossing-capacity and structure of the coal mine detecting and rescuing robot were redesigned and further improved. Using land surface mechanics theory and with reference to the principles of tracked vehicle, the kinematic and dynamic model of the robot were built according to the features of differential steering, which provided a basis for subsequent research on trajectory tracking of the coal mine detecting and rescuing robot.
Aiming at the features of non-structure environment in the coal mine, the hierarchical control system consisting of upper and lower computers was designed and a system architecture of layered cooperation and planning was proposed. Considering the particular application environment and demand, the control system was mainly composed of decision system (including monitor module of upper and lower computers, control module of the lower computer and sense and detection module, etc.), data communication system and motion control system. Then system architecture divided into such layers as decision layer, deliberation layer and control layer was proposed, which can meet the requirement of the navigation's complexity and uncertainty when the robot is under an unknown environment.
Combining with advantages of the representative optimization algorithm such as genetic algorithm and ant algorithm, improvements were made respectively. Firstly, an improved genetic algorithm was designed with the height variation of underground were fully considered. Three-dimensional workspace was modeled by grid method, and fitness function design used path length and energy consumption as the criterion. The initial population was generated by Variable length coding and random guided searching strategy to ensure the generation of the obstacle-free path in the initial period, meanwhile, crossover operator and mutation operator were optimized to solve the problems of the simple genetic algorithm such as premature phenomena and slow convergence, thus make the whole planning process more simple and effective. Secondly, an improved ant algorithm based on Max—Min Ant system(MMAS) was proposed. Its heuristic Function, selection rules of the path and the regeneration methods of pheromone were all improved, so that the convergence speed was increased and the performance of the path planning was improved. Finally the experimental results show that the performance of improved algorithms were effective and feasible.
A design method of fuzzy self-adaptive controller used in robot trajectory tracking was proposed. Firstly, the controller of the robot trajectory tracking control system was designed by Lyapunov direct method, which can control the process from current position to target point by the expected speed. When the reference speed was unequal to zero, Barbalat lemma was used to prove the global consistent asymptotic stability of the system. Furthermore, a fuzzy self-adaptive controller was designed on this basis, which solved problems such as the rules increased with the numbers of system's variables, and efficiency of the controller was greatly improved, fuzzy control logic also became more clear. The experimental results show these two trajectory tracking controller designed in this dissertation has excellent tracking effect for different initial errors and reference speeds.
本文以煤矿井下搜救探测机器人为研究对象,在对其运动装置进行设计分析的基础上,围绕移动机器人自主导航中的两项关键技术——路径规划与轨迹跟踪控制问题进行了深入的研究。首先对自主移动机器人研究中的关键技术进行了全面、系统的总结,重点对其中路径规划和轨迹跟踪控制的研究内容、存在问题及发展趋势等进行了综述,归纳总结了各种算法的性能差异,并以此为基础展开进一步的研究与探讨,主要研究内容包括以下几个方面：
提出了一种针对煤矿井下特殊环境的运动装置设计方案。对煤矿井下搜救探测机器人的运动系统、通行能力和结构特点进行了重新设计及进一步改进,并在此基础上,利用地面力学理论,参考履带车辆的运动学和动力学原理,针对煤矿井下搜救探测机器人采用差动转向的特点,建立了机器人的运动学和动力学模型,为后续的煤矿井下搜救探测机器人轨迹跟踪等控制问题的研究奠定了基础。
针对煤矿井下非结构化环境的不确定环境特征,设计了上下位机的分级控制系统,提出了一种分层协作规划与控制的体系结构。考虑到煤矿井下搜救探测机器人特定的应用环境及要求,设计了一个主要由决策系统(包括上位机监控模块、下位机控制模块、传感检测模块等)、数据通信系统和运动控制系统等组成的控制系统。并在分析当前出现的机器人各种体系结构的基础上,提出了一种从上到下依次分为决策层、慎思层和控制层的分层协作规划与控制的体系结构,能够满足机器人在未知环境下导航任务的复杂性与不确定性的要求。
结合目前具有代表性的遗传算法、蚁群算法这两种优化算法各自的特点,分别对其进行了改进。首先,设计了一种改进的遗传算法,充分考虑到井下环境地形的高低变化,采用栅格法在三维空间中对机器人工作环境进行建模,并根据路径长度最短且能耗最少的评价指标设计了适应度函数。按照可变长度的染色体编码方式及随机指导式搜索策略来生成初始种群,保证初始阶段无障碍路径的产生,同时针对传统遗传算法中存在的“早熟现象”和“收敛速度慢”的问题,将交叉算子和变异算子进行优化设计,从而使整个规划过程变得简单而有效。其次,本文还在最大—最小蚂蚁系统(MMAS)的基础上,提出了一种改进的蚁群算法,对其启发函数、路径选择规则及信息素更新方式等进行改进,加快了算法收敛速度,改善了路径规划的性能。最后通过实验对改进算法的性能进行了验证。
提出了一种用于实现机器人轨迹跟踪的模糊自适应控制器的设计方法。首先利用Lyapunov直接法设计出机器人轨迹跟踪控制系统的控制器,对机器人以期望运动速度从当前位置运动到目标点的过程进行控制,并在参考线速度不为零时,利用Barbalat引理对系统的全局一致渐近稳定性进行了证明。另外,在此基础上设计了一种模糊自适应控制器,解决了模糊多变量控制系统中规则数随系统变量数呈指数增长的问题,提高了控制器效率,且使模糊控制逻辑变得清晰明了。实验结果证明,本文设计的这两种轨迹跟踪控制器,对于不同初始误差、不同类型的参考速度都具有很好的跟踪效果。
China is the largest country of the coal production and consumption in the world. However, because of poor conditions of the coal mining system, large number of highly-gas mine and lack of effective techniques and management, especially continuous increasing demand for the coal, accidents such as gas explosion, water inflow and ignition have happened frequently in recent years. Heavy casualties and negative social effects have made healthy development of the coal industry impossible. Therefore it is premise and necessary to develop the coal mine detecting and rescuing robot. Under the circumstance the causes and field conditions of the coal mine accidents were unknown, it could substitute the rescue staff to enter the accident area for implementation of detecting and rescuing, and information can be transferred real-timely to the rescue command center simultaneously. It can provide scientific basis for the rescue decision, and the rescue plan can be made as rapidly and accurately as possible. Therefore it has critical significance for safety production in coal mine and can reduce loss of the public property and lives.
This dissertation focuses on the coal mine detecting and rescuing robot as research object, key techniques in robot autonomous navigation—path planning and trajectory tracking based on the design and analysis of its movement device were thoroughly and deeply studied. At first, the key techniques in autonomous mobile robot were summarized comprehensively and systematically, especially the research contents, existing problems and development trend of path planning and trajectory tracking were reviewed, performance differences in various algorithms were summarized and further research was developed. The main research contents included are as follows:
A kind of movement device aiming at special environment of the coal mine was proposed. The motion system, crossing-capacity and structure of the coal mine detecting and rescuing robot were redesigned and further improved. Using land surface mechanics theory and with reference to the principles of tracked vehicle, the kinematic and dynamic model of the robot were built according to the features of differential steering, which provided a basis for subsequent research on trajectory tracking of the coal mine detecting and rescuing robot.
Aiming at the features of non-structure environment in the coal mine, the hierarchical control system consisting of upper and lower computers was designed and a system architecture of layered cooperation and planning was proposed. Considering the particular application environment and demand, the control system was mainly composed of decision system (including monitor module of upper and lower computers, control module of the lower computer and sense and detection module, etc.), data communication system and motion control system. Then system architecture divided into such layers as decision layer, deliberation layer and control layer was proposed, which can meet the requirement of the navigation's complexity and uncertainty when the robot is under an unknown environment.
Combining with advantages of the representative optimization algorithm such as genetic algorithm and ant algorithm, improvements were made respectively. Firstly, an improved genetic algorithm was designed with the height variation of underground were fully considered. Three-dimensional workspace was modeled by grid method, and fitness function design used path length and energy consumption as the criterion. The initial population was generated by Variable length coding and random guided searching strategy to ensure the generation of the obstacle-free path in the initial period, meanwhile, crossover operator and mutation operator were optimized to solve the problems of the simple genetic algorithm such as premature phenomena and slow convergence, thus make the whole planning process more simple and effective. Secondly, an improved ant algorithm based on Max—Min Ant system(MMAS) was proposed. Its heuristic Function, selection rules of the path and the regeneration methods of pheromone were all improved, so that the convergence speed was increased and the performance of the path planning was improved. Finally the experimental results show that the performance of improved algorithms were effective and feasible.
A design method of fuzzy self-adaptive controller used in robot trajectory tracking was proposed. Firstly, the controller of the robot trajectory tracking control system was designed by Lyapunov direct method, which can control the process from current position to target point by the expected speed. When the reference speed was unequal to zero, Barbalat lemma was used to prove the global consistent asymptotic stability of the system. Furthermore, a fuzzy self-adaptive controller was designed on this basis, which solved problems such as the rules increased with the numbers of system's variables, and efficiency of the controller was greatly improved, fuzzy control logic also became more clear. The experimental results show these two trajectory tracking controller designed in this dissertation has excellent tracking effect for different initial errors and reference speeds.
引文
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