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Behavior-based autonomous cooperative control of intelligent mobile robot systems with embedded Petri nets

机译:嵌入式Petri网的基于行为的智能移动机器人系统自主协作控制

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This paper presents a methodology of distributed control system design for autonomous cooperative control of intelligent mobile robots. Following the natural concept of control architecture evolution, a bottom-up approach for control system design is presented. First, microcomputer based intelligent device modules, such as multiple infrared range finding sensor modules, and odometry and locomotor control modules, are constructed as a device manager layer on a distributed multi-microcontroller network based hardware structure to detect walls and obstacles and to move around the surroundings of a two-wheeled mobile robot. Then functional control modules, such as landmark and obstacle recognition and localization, robot motion control are implemented based on the device layer. Environment features such as lines and corners are estimated using a set of range sensors and a vision sensor. Next, some intelligent behavior modules, such as wall following, obstacle rounding, and target seeking, and environment mapping are implemented as cooperative activities based on the functional control modules. Upon these hierarchical activity modules, a non-centralized control approach is applied to implement the autonomous coordination of concurrent activities among behavior modules for the high-level tasks such as sensory navigation in unknown environments. The system integration and implementation issues are discussed for the proposed approach.
机译:本文提出了一种用于智能移动机器人自主协同控制的分布式控制系统设计方法。遵循控制体系结构演化的自然概念,提出了一种自下而上的控制系统设计方法。首先,将基于微计算机的智能设备模块(例如多个红外测距传感器模块,里程计和运动控制模块)构建为基于分布式多微控制器网络的硬件结构上的设备管理器层,以检测墙壁和障碍物并四处移动两轮移动机器人的周围环境。然后基于设备层实现功能控制模块,例如地标和障碍物识别与定位,机器人运动控制。使用一组距离传感器和视觉传感器来估算诸如线条和拐角之类的环境特征。接下来,基于功能控制模块,将一些智能行为模块(如墙跟踪,障碍物倒圆和目标搜索以及环境映射)实现为协作活动。在这些分层活动模块上,应用了非集中控制方法来实现行为模块之间并发活动的自主协调,以实现高级任务(例如未知环境中的感官导航)的行为模块之间的并发活动。针对所提出的方法讨论了系统集成和实现问题。

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