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Control theory and signal processing in machine vision for navigation
International Journal of Advanced Robotic Systems ( IF 2.1 ) Pub Date : 2020-07-01 , DOI: 10.1177/1729881420926470
Oleg Sergiyenko 1 , Wendy Flores-Fuentes 1 , Julio C Rodríguez-Quiñónez 1 , Moisés Rivas-López 1 , Lars Lindner 1
Affiliation  

Nowadays, mobile robotic systems use many complex electronic devices that employ a wide range of control and signal processing techniques to capture and process their environment in real time. Mobile robots use various types of sensory parts, such as CCD cameras, laser scanners, infrared, and ultrasonic sensors, as well as IMU and GPS devices. Also, a combination of the aforementioned sensory parts is used, which determines or measures the actual physical parameters of the environment as well as the current global position, orientation, and velocity of the mobile robot. Using mixed measurements of the actual physical parameters, different hardware processing units are utilized, implementing the suitable control algorithms to determine the control signals for the robot actuators and taking the decisions based on external conditions of the robotic system. Mobile robots, therefore, play a crucial role in modern industrial applications, as well as in others research and development applications. During the recent decade, unlike past robotic history, the word “robot” has gone through impressive mental transformation: In the mind of society and common people, it has gone from the meaning in science fiction and latest aerospace projects into a regular gadget, which can be found on the streets and even in homes. We are referring to the cleaner robots, smart domestic security and homework systems, handicap manipulators with voice control, and so on. As any other epochal phenomenon, obviously it has both positive and negative components. The positive one is that for common people the image of a rebel robot and dangerous machine is not there anymore. People can see that robots are now useful and sympathetic home inhabitants. However, the extremely important issue is that most of well-known fears of robotic fiction in real life is usually related to practical problems. The first of them is that of humans and robots interacting in the same area, and mutual interaction in dynamic environments. Of course, it is not so dramatic as it is in fiction. Robots do not cause disasters, yet physical body contacts or accidental collisions of robots and humans are not preferred. It causes many inconveniences and reduces the effectiveness when fulfilling their respective tasks simultaneously. Another great problem is recognition of environment by robots. It has many related aspects, such as erroneous distance interpretation, misunderstanding of object images, or detection faults of dangerous objects/situations among them. Of course, the robotic behavior, individual as well as in swarms, is a very complex area and has many difficult aspects. However, even the briefest analysis of the two abovementioned groups of problems shows us that they have the greatest priority and immediateness in a queue in order to harmonize the coexistence of robotic and biologic objects in the same space. The individual trajectories of the movement of robots and humans must be calculated in order so that it does not cause any inconveniences and undesired collisions during their performance and mutual assistance. It is obvious then that the relaxation of both problems could also be approached in two different ways:

中文翻译:

导航机器视觉中的控制理论与信号处理

如今,移动机器人系统使用许多复杂的电子设备,这些设备采用广泛的控制和信号处理技术来实时捕获和处理其环境。移动机器人使用各种类型的传感部件,例如 CCD 摄像头、激光扫描仪、红外线和超声波传感器,以及 IMU 和 GPS 设备。此外,使用上述传感部件的组合,确定或测量环境的实际物理参数以及移动机器人的当前全局位置、方向和速度。使用实际物理参数的混合测量,利用不同的硬件处理单元,实施合适的控制算法来确定机器人执行器的控制信号,并根据机器人系统的外部条件做出决定。因此,移动机器人在现代工业应用以及其他研发应用中发挥着至关重要的作用。近十年来,不同于以往的机器人历史,“机器人”这个词经历了令人印象深刻的心理转变:在社会和普通人的心目中,它从科幻小说和最新的航天项目中的意义变成了一个普通的小玩意,可以在街上,甚至在家里找到。我们指的是清洁机器人、智能家庭安全和家庭作业系统、带有语音控制的障碍操纵器等。与任何其他划时代的现象一样,显然,它既有积极的成分,也有消极的成分。积极的一点是,对于普通人来说,叛逆机器人和危险机器的形象已经不复存在了。人们可以看到机器人现在是有用且富有同情心的家庭居民。然而,极其重要的问题是,现实生活中对机器人小说的大多数众所周知的恐惧通常都与实际问题有关。第一个是人类和机器人在同一区域交互,在动态环境中相互交互。当然,它不像小说中那么戏剧化。机器人不会造成灾难,但机器人与人类的身体接触或意外碰撞不是首选。在同时完成各自的任务时,它会造成许多不便并降低效率。另一个大问题是机器人对环境的识别。它有很多相关的方面,例如错误的距离解释,对物体图像的误解,或其中危险物体/情况的检测故障。当然,机器人行为,无论是个体还是群体,都是一个非常复杂的领域,有许多困难的方面。然而,即使对上述两组问题进行最简短的分析也表明,它们在队列中具有最大的优先级和即时性,以协调机器人和生物对象在同一空间中的共存。机器人和人类运动的个体轨迹必须按顺序计算,以便在它们的表演和互助过程中不会造成任何不便和意外碰撞。
更新日期:2020-07-01
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