Navigation and learning experiments by an autonomous robot

Developing an autonomous mobile robot capable of navigation, surveillance and manipulation in complex and dynamic environments is a key research activity at CESAR, Oak Ridge National Laboratory's Center for Engineering Systems Advanced Research. The latest series of completed experiments was performed using the autonomous mobile robot HERMIES-IIB (Hostile Environment Robotic Intelligence Experiment Series II-B).     

Dynamic omnidirectional vision for mobile robots

Mobile robotic devices hold great promise for a variety of applications in industry. A key step in the design of a mobile robot is to determine the navigation method for mobility control. The purpose of this paper is to describe a new algorithm for omnidirectional vision navigation. A prototype omnidirectional vision system and the implementation of the navigation techniques using this modern sensor and an advanced automatic image processor is described. The significance of this work is in the development of a new and novel approach—dynamic omnidirectional vision for mobile robots and autonomous guided vehicles.     

A digital retina-like low-level vision processor

This correspondence presents the basic design and the simulation of a low level multilayer vision processor that emulates to some degree the functional behavior of a human retina. This retina-like multilayer processor is the lower part of an autonomous self-organized vision system, called Kydon, that could be used on visually impaired people with a damaged visual cerebral cortex. The Kydon vision system, however, is not presented in this paper. The retina-like processor consists of four major layers, where each of them is an array processor based on hexagonal, autonomous processing elements that perform a certain set of low level vision tasks, such as smoothing and light adaptation, edge detection, segmentation, line recognition and region-graph generation. At each layer, the array processor is a 2D array of k/spl times/m hexagonal identical autonomous cells that simultaneously execute certain low level vision tasks. Thus, the hardware design and the simulation at the transistor level of the processing elements (PEs) of the retina-like processor and its simulated functionality with illustrative examples are provided in this paper.     

全自主移动机器人分层递阶控制研究

本文提出了一种基于多CPU的分层递阶控制策略,应用于全自主移动机器人的结构化设计。以分层递阶控制为核心思想的自主机器人采用智能级、协调级和执行级级连的结构,其中智能级和协调级配备独立的微处理器。实验表明,所设计的自主机器人系统具备良好的环境感知能力和控制精度,可以通过开放的VC++平台实现对机器人的控制。     

Fuzzy logic path tracking control for autonomous non-holonomic mobile robots: Design of System on a Chip

This paper presents a System on Chip (SoC) for the path following task of autonomous non-holonomic mobile robots. The SoC consists of a parameterized Digital Fuzzy Logic Controller (DFLC) core and a flow control algorithm that runs under the Xilinx Microblaze soft processor core. The fuzzy controller supports a fuzzy path tracking algorithm introduced by the authors. The FPGA board hosting the SoC was attached to an actual differential-drive Pioneer 3-DX8 robot, which was used in field experiments in order to assess the overall performance of the tracking scheme. Moreover, quantization problems and limitations imposed by the system configuration are also discussed.     

基于嵌入式的移动机器人导航算法研究

针对移动机器人视觉导航中路径识别和路径跟踪问题,采用S3C2440嵌入式处理器处理摄像头传感器采集的路径环境信息,实现移动机器人在有引导路径的情况下自主导航。首先,用小波分析的方法进行图像增强和滤波,数学形态学反复开关滤波去除路面上的杂质,其次,针对单路径和交叉引导路径分别采用基于阈值化和形态学方法提取中心点,最后,加权最小二乘法计算导航参数。实验结果表明,该导航算法具有较好的实时性和准确的控制精度,能够满足机器人视觉导航的需要。     

WSN in cyber physical systems: Enhanced energy management routing approach using software agents

Recently, the cyber physical system has emerged as a promising direction to enrich the interactions between physical and virtual worlds. Meanwhile, a lot of research is dedicated to wireless sensor networks as an integral part of cyber physical systems. A wireless sensor network (WSN) is a wireless network consisting of spatially distributed autonomous devices that use sensors to monitor physical or environmental conditions. These autonomous devices, or nodes, combine with routers and a gateway to create a typical WSN system. Shrinking size and increasing deployment density of wireless sensor nodes implies the smaller equipped battery size. This means emerging wireless sensor nodes must compete for efficient energy utilization to increase the WSN lifetime. The network lifetime is defined as the time duration until the first sensor node in a network fails due to battery depletion. One solution for enhancing the lifetime of WSN is to utilize mobile agents. In this paper, we propose an agent-based approach that performs data processing and data aggregation decisions locally i.e., at nodes rather than bringing data back to a central processor (sink). Our proposed approach increases the network lifetime by generating an optimal routing path for mobile agents to transverse the network. The proposed approach consists of two phases. In the first phase, Dijkstra’s algorithm is used to generate a complete graph to connect all source nodes in a WSN. In the second phase, a genetic algorithm is used to generate the best-approximated route for mobile agents in a radio harsh environment to route the sensory data to the base-station. To demonstrate the feasibility of our approach, a formal analysis and experimental results are presented.     

室内自主式移动机器人定位方法

定位是确定机器人在其工作环境中所处位置的过程.应用各种传感器感知信息实现可靠的定位是自主式移动机器人最基本、也是最重要的一项功能之一.本文对室内自主式移动机器人的定位技术进行了综述,介绍了当前自主式移动机器人定位方法的研究现状.同时,对国内外具有典型性的研究方法进行了较洋细的介绍,并重点提出了几种室内自主式移动机器人通用的定位方法,对其中的地图构造、位姿估计方法进行了详细介绍.最后,论述了自主式移动机器人定位系统与地图构造中所面临的主要问题及其解决方法并指出了该领域今后的研究方向.     

面向移动终端的统计机器翻译解码定点化方法

面向移动终端的统计机器翻译需求越来越多,但无浮点运算单元的处理器限制了翻译速度。该文提出了一种对统计机器翻译解码运算的定点化运算方法,缓解了无浮点运算单元的处理器对翻译速度的影响。基于PC和移动终端的实验表明,在保证翻译质量的情况下,利用定点处理浮点运算的解码器的运算速度较编译器模拟的浮点运算速度提高135.6%。因此,该方法可以有效地提高浮点运算能力薄弱的移动终端统计机器翻译速度。     

Development of A Behavior‐Based Cooperative Search Strategy for Distributed Autonomous Mobile Robots Using Zigbee Wireless Sensor Network

To achieve efficient and objective search tasks in an unknown environment, a cooperative search strategy for distributed autonomous mobile robots is developed using a behavior‐based control framework with individual and group behaviors. The sensing information of each mobile robot activates the individual behaviors to facilitate autonomous search tasks to avoid obstacles. An 802.15.4 ZigBee wireless sensor network then activates the group behaviors that enable cooperative search among the mobile robots. An unknown environment is dynamically divided into several sub‐areas according to the locations and sensing data of the autonomous mobile robots. The group behaviors then enable the distributed autonomous mobile robots to scatter and move in the search environment. The developed cooperative search strategy successfully reduces the search time within the test environments by 22.67% (simulation results) and 31.15% (experimental results).     

The integration of dissimilar control architectures for mobile robot applications

This article discusses a dual architecture for autonomous mobile robots. The implementation application is an autonomous visual inspection system for waste stored in drums. We discuss the three main architectures commonly implemented on mobile robots. The various modules needed for the successful operation of a mobile robot are analyzed, and software and hardware requirements for each modules are noted. We make arguments as to which architecture is best suited for each component. From the results of this analysis, we propose a new dual architecture for autonomous mobile robots. Rather than developing a single hybrid architecture that has qualities of both behavioral and functional architectures, we have taken an approach that involves the integration of two distinct architectures. Next, we detail the implementation of the architecture of the robot, and the advantages of our architecture as it pertains to the integration of system components. System performance in the testing environment is discussed. © 1997 John Wiley & Sons, Inc.     

Cofields: a physically inspired approach to motion coordination

As computing becomes increasingly pervasive, autonomous computers are going to be embedded in everyday objects in our physical environment. In such scenarios, mobility itself will be pervasive. Mobile users, mobile devices, computer-enabled vehicles, and mobile software components will define a dynamic, networked world in which a large set of autonomous components will interact with each other to orchestrate their activities. We focus on the problem of coordinating autonomous agent's movements in a distributed environment. Orchestrating mobile autonomous agents can take inspiration from the laws of physics. Agent's movements could be driven by locally perceived computational force fields, or cofields, generated by the agents themselves and propagated through an embedded infrastructure.     

Autonomous power management in mobile devices using dynamic frequency scaling and reinforcement learning for energy minimization

Embedded systems execute applications that execute hardware differently depending on the computation task, generating time-varying workloads. Energy minimization can be reached by using the low-power central processing unit (CPU) frequency for each workload. We propose an autonomous and online approach, capable of reducing energy consumption from adaptation to workload variations even in an unknown environment. In this approach, we improved the AEWMA algorithm into a new algorithm called AEWMA-MSE, adding new functionality to detect workload changes and demonstrating why it is better to use statistical analysis for real user cases in a mobile environment. Also, a new power model for mobile devices based on k-NN algorithm for regression was proposed and validated proving to have a better trade-off between execution time and precision than neural networks and linear regression-based models. AEWMA-MSE and the proposed power model are integrated into a novel algorithm for energy management based on reinforcement learning that suitably selects the appropriate CPU frequency based on workload predictions to minimize energy consumption. The proposed approach is validated through simulation by using real smartphone data from an ARM Cortex A7 processor used in a commercial smartphone. Our proposal proved to have an improvement in the Q-learning cost function and can effectively minimize the average energy consumption by 21% and up to 29% when compared to the already existing approaches.     

自主移动机器人局部路径规划综述

自主移动机器人技术是近年来的研究热点,而路径规划技术是自主移动机器人技术研究中的一个重要内容。讨论了自主移动机器人路径规划技术的分类和研究局部路径规划的重要性;分析了局部路径规划技术的发展现状;指出了局部路径规划各种方法的优点与不足;对局部路径规划技术今后的发展方向做出了展望。     

基于深度学习的移动机器人自主导航实验平台

随着移动机器人的发展,其应用场景越来越复杂,对自主导航这一关键技术提出了更高要求。本文搭建了移动机器人实验平台,设计了基于深度学习的自主导航方法,将RGB图像作为卷积神经网络模型的输入,即可直接输出导航控制信号,不仅降低硬件成本,而且避免复杂的特征工程和规划策略。实验结果表明该平台具有良好的自主导航性能,对移动机器人适...     

Preprocessing of alphanumeric images to be recognized by autonomous computing systems

Methods and algorithms for digital image processing that increase the probability of correct recognition of alphanumeric data are considered. The computational costs of the control block of an autonomous image recognition system based on TMS320C5416 signal processor are analyzed. Natalia S. Novozhilova. Born 1955. Graduated from Moscow Institute of Electronic Engineering in 1978. Received her candidate’s degree (Mathematics and Physics) in 1984. At present, she is a senior researcher at Lukin Scientific Research Institute of Physical Problems. Scientific interests: pattern recognition and mathematical methods for processing the results of a physical experiment. Author of 22 publications. Aleksandr G. Safonov. Born 1952. Graduated from Moscow Power Engineering Institute in 1975. Received his candidate’s degree (Technical Sciences) in 1982. At present, he is a head of department at Lukin Scientific Research Institute of Physical Problems. Scientific interests: automated data processing complexes, pattern recognition, and microelectronics. Author of more than 50 publications.     

一种基于声纳信息的地图创建方法

地图创建是实现机器人在未知环境中自主导航的关键。该文对移动机器人在地图创建中所收集的不确定传感信息进行研究,分析声纳传感器的散射和镜面反射特性,提出一种改进的概率栅格的地图创建方法。该方法将距离信任因子引入到声纳传感器模型。利用该模型,实现移动机器人的自主地图创建,并有效地减少由于声纳传感器所引起的不确定性。通过机器人平台上进行的实验表明该方法的有 效性。     

激光即时定位与建图算法综述

激光即时定位与建图(SLAM)算法是一种在机器人导航和自主驾驶领域被广泛应用的技术;该技术可以利用激光雷达扫描环境并提取特征点,实现机器人的自主定位和地图构建;针对机器人激光SLAM技术进行研究,分析了各个激光SLAM算法的基本原理,并且对主流SLAM算法进行了现状总结;根据激光SLAM算法的特点以及原理不同,将激光SLAM算法分为：基于滤波器的算法、基于图优化的算法、基于配准的算法、基于学习的算法等;基于上述分类,详细介绍了每个算法的优缺点,并且分述了近两年的主要研究成果;针对移动机器人激光SLAM算法研究现状,对激光SLAM算法的未来发展进行了展望。     

A system for self-diagnosis of an autonomous mobile robot using an internal state sensory system: fault detection and coping with the internal condition

Considering that intelligent robotic systems work in a real environment, it is important that they themselves have the ability to determine their own internal conditions. Therefore, we consider it necessary to pay some attention to the diagnosis of such intelligent systems and to construct a system for the self-diagnosis of an autonomous mobile robot. Autonomous mobile systems must have a self-contained diagnostic system and therefore there are restrictions to building such a system on a mobile robot. In this paper, we describe an internal state sensory system and a method for diagnosing conditions in an autonomous mobile robot. The prototype of our internal sensory system consists of voltage sensors, current sensors and encoders. We show experimental results of the diagnosis using an omnidirectional mobile robot and the developed system. Also, we propose a method that is able to cope with the internal condition using internal sensory information. We focus on the functional units in a single robot system and also examine a method in which the faulty condition is categorized into three levels. The measures taken to cope with the faulty condition are set for each level to enable the robot to continue to execute the task. We show experimental results using an omnidirectional mobile robot with a self-diagnosis system and our proposed method.