多机器人协同覆盖技术研究
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摘要
本论文来源于国家基础研究项目“异质多移动体的协同机制与重构技术基础研究”(A1420060159),属于其子任务“多机器人协同”的研究方向。本文主要研究了以“覆盖”为目标任务的多机器人体系结构、通信链路、地图表示、覆盖单元分解与分配以及覆盖效果评价等问题。目的在于探索多机器人协同协作进行覆盖任务的有效方法,构建适合覆盖任务的多机器人体系结构,通信模式以及地图知识表示方法,从而提高多机器人的协同协作水平,最终实现优化覆盖的目的。
合理的体系结构是多机器人协同完成覆盖任务至关重要的基础,本文首先将自组重构策略引入分层式多机器人体系结构,形成自组分层式结构。系统由上而下分成三层:指挥层、协调层和执行层,采用“指令”通信模式和自适应重组的策略来实现协作任务。仿真实验表明自组分层式多机器人体系具有较高的鲁棒性和容错性,对任务和环境具有较好自适应性。通信是多机器人能实现有效协同协作的关键,同时也是自组分层式系统的最基本要求。针对实际覆盖任务中多机器人通信可能中断的情况下,提出CAM策略、CSM策略和SSS策略三种机器人按需主动建立通信链路的方法来保障系统的正常运行。
机器人覆盖离不开环境知识,环境知识的表示方法即地图表示方法对已知环境中的多机器人覆盖尤其重要。因此,论文针对多机器人覆盖提出了4维环境地图的地图表示方法。空间点的4维坐标由3维空间坐标和1维环境特征值构成。3维空间坐标由机器人的测距传感器观测获得,同时利用多传感器信息获得该点的1维环境特征值。观测获得环境中许多空间点的4维坐标数据,并采用完全二叉树结构进行存储后,就获得该区域的4维环境地图。4维环境地图通过Krige法进行插值可生成栅格地图、利用高程变异算子可生成单元分解地图以及通过二叉树查找可生成拓扑地图。这些地图,特别是单元分解地图,都是许多研究者热衷于研究的机器人覆盖地图。
在4维环境地图的基础上,研究了变长切线的单元分解方法。变长切线法通过“切线扫掠”目标区域,按一定规则选取由切线与障碍区产生的切点或交点作为关键点来进行单元分解。而在4维环境地图中,可以通过简单的循环二叉树查找来获得这些关键点的坐标值。与目前公认较优的Boustrophedon单元分解法相比,变长切线法单元分解不仅算法更为简单而且分解出的单元数目大大减少。这大大降低多机器人覆盖单元分配的复杂度,使系统可以用较小的计算量来获得较优的分配与规划。在自组分层式系统中,针对单元数量与机器人数量的不同关系,分n≈m、n》m和n《m3种情况分别分析讨论了基于近似矩形化单元面积估计的单元分配策略。对模拟环境进行了不同数量的多机器人协同覆盖仿真测试,各种情况下的多机器人系统均能成功实现对目标区域的覆盖。而后,尝试研究了多机器人在未知环境下的覆盖策略。在基于Morse理论利用测距传感器获得环境关键点的基础上,提出切线覆盖和波纹覆盖2种未知环境的覆盖方法。由于机器人进行测距等观测的同时,实际也完成了4维环境地图的建图,所以这类覆盖方法又称为同时覆盖与建图。
最后,为分析评价机器人对目标区域的覆盖效果,利用甘特图来描述多机器人系统覆盖过程。并研究了覆盖率、时耗比、能耗比以及有效路径比等定量分析覆盖效果的评价因子。并特别针对多机器人协同覆盖,提出覆盖协同指数CCI这一综合评价因子。
The thesis was supported by national basic research project "Research on Basis of Synergetic Task and Reconfiguration Techniques for Heterogeneous Multi-mobile Agents"(A1420060159). Related works was subject to the part "multi-robots synergetic task" of the project. The thesis focuses on the problems of multi-robots coverage based multi-robots architecture、robot communication link、robot map description、coverage cell decomposition、coverage cell allocation and coverage performance metrics. The objectives are exploring new effective methods of robot coverage based on multi-robots synergetic cooperation in designated environments, and improving the cooperation of multi-robots, advancing the efficiency of robot coverage, achieving optimal coverage at last.
The architecture is absolutely necessary basic of multi-robots coverage. In the thesis, firstly a self-configuration strategy was loaded on the layered architecture of multi-robot. Then a self-configurable and layered architecture of multi-robot (SCLA) was presented. Command layer, coordinate layer and execute layer are the three layers of SCLA from up to down. Instruction communication and self-configuration strategy are adopted by SCLA to achieve synergic mission. The simulation results indicate that it is robust, fault-tolerant to environment and mission. Communication is the key technology in multi-robots coordination and cooperation, and also is the basis of SCLA. In order to deal with some circumstances such as multi-robots communicating failure, CAM、CSM and SSS are presented, which are three strategies of robots establish communication links on-demand. So, the SCLA can run in all cases.
Robot coverage needs environmental knowledge. The organization and description of environmental knowledge are called robot map. It is more important to the robot coverage. So, the 4-D environmental map for coverage is researched in this thesis. 4-D environmental map are composed from 3-D space coordinates and 1-D characteristics of the environment. The 3-D space coordinates can be observed by the robot's distance sensor, while the 1-D characteristics of the environment can be observed by using multi-sensor information at the same time. After sampling 4-D coordinate data of points in environment, and storing as a fully binary tree structure, a 4-D environmental map is attained for a environment region. Then some map transform methods from 4-D environmental map are discussed separately. They are grid map generating by Krige interpolation, cell decomposition map generating by elevation mutation operator, and topological map generating by binary tree finding. These maps, especially the cell decomposition map, are always used in robot coverage by many researchers.
Length shift tangent (LST) cell decomposition is researched based on 4-D environmental map. According to certain rules, points of tangency or intersection with obstacle area are selected as the key points to cell decomposition by sweeping the target area with a tangent that shifts length timely. In 4-D environmental map, these key points can be got by binary tree finding simply. Compared to Boustrophedon cell decomposition, which is regarded as an excellent coverage method, LST cell decomposition not only reduced the complexity of algorithm but also decreased the number of cells. All these make robots system allocating and planning more optimal with smaller cost. In the SCLA system, cell allocation strategies based on cell square estimating by approximately rectangular are studied separately for n≈m, n>>m and n< At last, in order to analyze and estimate the performance of multi-robots coverage in designated region, Gantt chart is used to describe the process of multi-robots coverage. And some measure and metrics are presented such as coverage rateη_(cs), time consumption ratioη_T, energy consumption ratioη_E and effective path ratioη_(?). They are used to estimate the performance quantitatively. Then the coverage coordination index CCI is proposed, specifically for multi-robots synergetic coverage.
合理的体系结构是多机器人协同完成覆盖任务至关重要的基础,本文首先将自组重构策略引入分层式多机器人体系结构,形成自组分层式结构。系统由上而下分成三层:指挥层、协调层和执行层,采用“指令”通信模式和自适应重组的策略来实现协作任务。仿真实验表明自组分层式多机器人体系具有较高的鲁棒性和容错性,对任务和环境具有较好自适应性。通信是多机器人能实现有效协同协作的关键,同时也是自组分层式系统的最基本要求。针对实际覆盖任务中多机器人通信可能中断的情况下,提出CAM策略、CSM策略和SSS策略三种机器人按需主动建立通信链路的方法来保障系统的正常运行。
机器人覆盖离不开环境知识,环境知识的表示方法即地图表示方法对已知环境中的多机器人覆盖尤其重要。因此,论文针对多机器人覆盖提出了4维环境地图的地图表示方法。空间点的4维坐标由3维空间坐标和1维环境特征值构成。3维空间坐标由机器人的测距传感器观测获得,同时利用多传感器信息获得该点的1维环境特征值。观测获得环境中许多空间点的4维坐标数据,并采用完全二叉树结构进行存储后,就获得该区域的4维环境地图。4维环境地图通过Krige法进行插值可生成栅格地图、利用高程变异算子可生成单元分解地图以及通过二叉树查找可生成拓扑地图。这些地图,特别是单元分解地图,都是许多研究者热衷于研究的机器人覆盖地图。
在4维环境地图的基础上,研究了变长切线的单元分解方法。变长切线法通过“切线扫掠”目标区域,按一定规则选取由切线与障碍区产生的切点或交点作为关键点来进行单元分解。而在4维环境地图中,可以通过简单的循环二叉树查找来获得这些关键点的坐标值。与目前公认较优的Boustrophedon单元分解法相比,变长切线法单元分解不仅算法更为简单而且分解出的单元数目大大减少。这大大降低多机器人覆盖单元分配的复杂度,使系统可以用较小的计算量来获得较优的分配与规划。在自组分层式系统中,针对单元数量与机器人数量的不同关系,分n≈m、n》m和n《m3种情况分别分析讨论了基于近似矩形化单元面积估计的单元分配策略。对模拟环境进行了不同数量的多机器人协同覆盖仿真测试,各种情况下的多机器人系统均能成功实现对目标区域的覆盖。而后,尝试研究了多机器人在未知环境下的覆盖策略。在基于Morse理论利用测距传感器获得环境关键点的基础上,提出切线覆盖和波纹覆盖2种未知环境的覆盖方法。由于机器人进行测距等观测的同时,实际也完成了4维环境地图的建图,所以这类覆盖方法又称为同时覆盖与建图。
最后,为分析评价机器人对目标区域的覆盖效果,利用甘特图来描述多机器人系统覆盖过程。并研究了覆盖率、时耗比、能耗比以及有效路径比等定量分析覆盖效果的评价因子。并特别针对多机器人协同覆盖,提出覆盖协同指数CCI这一综合评价因子。
The thesis was supported by national basic research project "Research on Basis of Synergetic Task and Reconfiguration Techniques for Heterogeneous Multi-mobile Agents"(A1420060159). Related works was subject to the part "multi-robots synergetic task" of the project. The thesis focuses on the problems of multi-robots coverage based multi-robots architecture、robot communication link、robot map description、coverage cell decomposition、coverage cell allocation and coverage performance metrics. The objectives are exploring new effective methods of robot coverage based on multi-robots synergetic cooperation in designated environments, and improving the cooperation of multi-robots, advancing the efficiency of robot coverage, achieving optimal coverage at last.
The architecture is absolutely necessary basic of multi-robots coverage. In the thesis, firstly a self-configuration strategy was loaded on the layered architecture of multi-robot. Then a self-configurable and layered architecture of multi-robot (SCLA) was presented. Command layer, coordinate layer and execute layer are the three layers of SCLA from up to down. Instruction communication and self-configuration strategy are adopted by SCLA to achieve synergic mission. The simulation results indicate that it is robust, fault-tolerant to environment and mission. Communication is the key technology in multi-robots coordination and cooperation, and also is the basis of SCLA. In order to deal with some circumstances such as multi-robots communicating failure, CAM、CSM and SSS are presented, which are three strategies of robots establish communication links on-demand. So, the SCLA can run in all cases.
Robot coverage needs environmental knowledge. The organization and description of environmental knowledge are called robot map. It is more important to the robot coverage. So, the 4-D environmental map for coverage is researched in this thesis. 4-D environmental map are composed from 3-D space coordinates and 1-D characteristics of the environment. The 3-D space coordinates can be observed by the robot's distance sensor, while the 1-D characteristics of the environment can be observed by using multi-sensor information at the same time. After sampling 4-D coordinate data of points in environment, and storing as a fully binary tree structure, a 4-D environmental map is attained for a environment region. Then some map transform methods from 4-D environmental map are discussed separately. They are grid map generating by Krige interpolation, cell decomposition map generating by elevation mutation operator, and topological map generating by binary tree finding. These maps, especially the cell decomposition map, are always used in robot coverage by many researchers.
Length shift tangent (LST) cell decomposition is researched based on 4-D environmental map. According to certain rules, points of tangency or intersection with obstacle area are selected as the key points to cell decomposition by sweeping the target area with a tangent that shifts length timely. In 4-D environmental map, these key points can be got by binary tree finding simply. Compared to Boustrophedon cell decomposition, which is regarded as an excellent coverage method, LST cell decomposition not only reduced the complexity of algorithm but also decreased the number of cells. All these make robots system allocating and planning more optimal with smaller cost. In the SCLA system, cell allocation strategies based on cell square estimating by approximately rectangular are studied separately for n≈m, n>>m and n<
引文
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