PATH FOLLOWING GPS-BASED CONTROL OF SMALL-SIZE ROBOTIC UNMANNED BLIMP

Robotic unmanned blimps own an enormous potential for applications in low-speed and low-altitude exploration, surveillance, and monitoring, as well as telecommunication relay platforms. To make lighter-than-air platform a robotic blimp with significant levels of autonomy, the decoupled longitude and latitude dynamic model is developed, and the hardware and software of the flight control system are designed and detailed. Flight control and navigation strategy and algorithms for waypoint flight problem are discussed. A result of flight experiment is also presented, which validates that the flight control system is applicable and initial machine intelligence of robotic blimp is achieved.

Human-Robot Interface for Unmanned Aerial Vehicle via a Leap Motion

The unmanned aircraft vehicles industry is in the ascendant while traditional interaction ways for an unmanned aerial vehicle(UAV)are not intuitive enough.It is difficult for a beginner to control a UAV,therefore natural interaction methods are preferred.This paper presents a novel interactive control method for a UAV through operator's gesture,and explores the natural interaction method for the UAV.The proposed system uses the leap motion controller as an input device acquiring the gesture position and orientation data.It is found that the proposed human-robot interface can track the movement of the operator with satisfactory accuracy.The biggest advantage of the proposed method is its capability to control the UAV by just one hand instead of a joystick.A series of experiments verified the feasibility of the proposed human-robot interface.The results demonstrate that non-professional operators can easily operate a remote UAV by just using this system.

Using Unmanned Underwater Vehicles as Research Platforms in Coastal Ocean Studies

The advantages of using unmanned underwater vehicles in coastal ocean studies are emphasized. Two types of representative vehicles, remotely operated vehicle (ROV) and autonomous underwater vehicle (AUV) from University of South Florida, are discussed. Two individual modular sensor packages designed and tested for these platforms and field measurement results are also presented. The bottom classification and albedo package, BCAP, provides fast and accurate estimates of bottom albedos, along with other parameters such as in-water remote sensing reflectance. The real-time ocean bottom optical topographer, ROBOT, reveals high-resolution 3-dimentional bottom topography for target identification. Field data and results from recent Coastal Benthic Optical Properties field campaign, 1999 and 2000, are presented. Advantages and limitations of these vehicles and applications of modular sensor packages are compared and discussed.

Quantum Cooperative Robotics and Autonomy

The intersection of Quantum Technologies and Robotics Autonomy is explored in the present paper.The two areas are brought together in establishing an interdisciplinary interface that contributes to advancing the field of system autonomy,and pushes the engineering boundaries beyond the existing techniques.The present research adopts the experimental aspects of quantum entanglement and quantum cryptography,and integrates these established quantum capabilities into distributed robotic platforms,to explore the possibility of achieving increased autonomy for the control of multi-agent robotic systems engaged in cooperative tasks.Experimental quantum capabilities are realized by producing single photons(using spontaneous parametric down-conversion process),polarization of photons,detecting vertical and horizontal polarizations,and single photon detecting/counting.Specifically,such quantum aspects are implemented on network of classical agents,i.e.,classical aerial and ground robots/unmanned systems.With respect to classical systems for robotic applications,leveraging quantum technology is expected to lead to guaranteed security,very fast control and communication,and unparalleled quantum capabilities such as entanglement and quantum superposition that will enable novel applications.

Robot Pilot:A New Autonomous System toward Flying Manned Aerial Vehicles

The robot pilot is a new concept of a robot system that pilots a manned aircraft,thereby forming a new type of unmanned aircraft system(UAS)that makes full use of the platform maturity,load capacity,and airworthiness of existing manned aircraft while greatly expanding the operation and application fields of UASs.In this research,the implementation and advantages of the robot pilot concept are discussed in detail,and a helicopter robot pilot is proposed to fly manned helicopters.The robot manipulators are designed according to the handling characteristics of the helicopter-controlling mechanism.Based on a kinematic analysis of the robot manipulators,a direct-driving method is established for the robot flight controller to reduce the time delay and control error of the robot servo process.A supporting ground station is built to realize different flight modes and the functional integration of the robot pilot.Finally,a prototype of the helicopter robot pilot is processed and installed in a helicopter to carry out flight tests.The test results show that the robot pilot can independently fly the helicopter to realize forward flight,backward flight,side flight,and turning flight,which verifies the effectiveness of the helicopter robot pilot.

Telepresence Robots and Controlling Techniques in Healthcare System

In this era of post-COVID-19,humans are psychologically restricted to interact less with other humans.According to the world health organization(WHO),there are many scenarios where human interactions cause severe multiplication of viruses from human to human and spread worldwide.Most healthcare systems shifted to isolation during the pandemic and a very restricted work environment.Investigations were done to overcome the remedy,and the researcher developed different techniques and recommended solutions.Telepresence robot was the solution achieved by all industries to continue their operations but with almost zero physical interaction with other humans.It played a vital role in this perspective to help humans to perform daily routine tasks.Healthcare workers can use telepresence robots to interact with patients who visit the healthcare center for initial diagnosis for better healthcare system performance without direct interaction.The presented paper aims to compare different telepresence robots and their different controlling techniques to perform the needful in the respective scenario of healthcare environments.This paper comprehensively analyzes and reviews the applications of presented techniques to control different telepresence robots.However,our feature-wise analysis also points to specific technical,appropriate,and ethical challenges that remain to be solved.The proposed investigation summarizes the need for further multifaceted research on the design and impact of a telepresence robot for healthcare centers,building on new perceptions during the COVID-19 pandemic.

Intelligent Detection Method of Substation Environmental Targets Based on MD-Yolov7

The complex operating environment in substations, with different safety distances for live equipment, is a typical high-risk working area, and it is crucial to accurately identify the type of live equipment during automated operations. This paper investigates the detection of live equipment under complex backgrounds and noise disturbances, designs a method for expanding lightweight disturbance data by fitting Gaussian stretched positional information with recurrent neural networks and iterative optimization, and proposes an intelligent detection method for MD-Yolov7 substation environmental targets based on fused multilayer feature fusion (MLFF) and detection transformer (DETR). Subsequently, to verify the performance of the proposed method, an experimental test platform was built to carry out performance validation experiments. The results show that the proposed method has significantly improved the performance of the detection accuracy of live devices compared to the pairwise comparison algorithm, with an average mean accuracy (mAP) of 99.2%, which verifies the feasibility and accuracy of the proposed method and has a high application value.

Design and Simulation of Insulator Cleaning Robot via Pro/E and ADAMS

Aiming at the complicated cleaning environment of high-voltage substation insulators,the cleaning robot design principles are put for ward.On this basis,the structure framework of cleaning robot is proposed,and its system composition is introduced,mainly including mobile mechanism,clamping mechanism and cleaning mechanism.The structure has the characteristics of light weight,small size and self-locking without motor.Pro/E software is used to complete the modeling of the cleaning robot.Finally,ADAMS is used to establish the simulation model for the cleaning robot,its moving and cleaning process on high-voltage substation insulators is simulated,and the simulation results are analyzed.The results show that the structural design of the cleaning robot is reasonable.

无人驾驶农机避障路径跟踪仿真与验证

【目的】为便于验证无人驾驶农机避障路径跟踪的效果,减少实际无人农机试验次数与消耗,设计一种无人驾驶农机避障路径跟踪仿真验证方法,构建一个仿真验证应用系统。【方法】以无人农机为基础,集成真实复杂地形环境仿真、实际作业农机仿真和路径规划算法植入,构建一个一体化仿真验证应用系统。基于三维SLAM技术,采集环境点云数据,实现农田地形环境仿真建模,构建阿克曼转向机械结构的农机仿真建模,提出一种基于农机动力学约束的TEB局部路径规划算法;在仿真验证应用系统中实现路径规划跟踪及避障,并通过多次测试验证该算法的有效性。【结果】避障路径跟踪有效性对比测试和避障路径跟踪平顺性验证测试结果表明,无人农机行驶过程中可有效动态避障,最短有效避障距离为4.1 m。路径跟踪控制效果良好,障碍物距离大于5.0 m时,可控平均误差≤0.4305 m,均方根误差≤0.3151 m;障碍物距离在4.5~5.0 m时,可控误差均值≤1.3538 m,均方根误差≤1.6126 m。【结论】本文提出的改进TEB算法具有较强的作业能力以及较高的作业精度,满足农业机械导航避障路径跟踪仿真验证的需求,该算法可应用于无人农机在实际农田环境的避障路径跟踪。该应用系统易于扩充,为精准农业中针对各种复杂作业环境的农机运作状态的优化设计研究提供基础。

小型无人有缆遥控水下机器人智能控制方法

针对深度确定性策略梯度(DDPG)算法应用于无人有缆遥控水下机器人(ROV)运动控制时存在的坏样本影响学习稳定性、缺少环境探索能力以及学习时间长难收敛等问题,从神经网络结构、噪声引入和融合监督学习3个方面对DDPG算法进行改进,并提出了基于混合神经网络结构和参数噪声的监督式DDPG算法。仿真结果表明,监督式DDPG算法比常规DDPG算法和传统比例-积分-微分(PID)算法更加有效。

变电站巡检机器人室内外无缝定位算法研究

为提高巡检机器人在变电站室内外交互的复杂场景下的定位性能,提出了一种基于传感器精度和多源信息融合的无缝定位方案,通过室外GPS/IMU组合定位和室内AMCL定位的平稳切换,实现了巡检机器人在变电站室内外交互环境下的无缝定位。同时针对定位过程中的机器人绑架问题,利用GPS定位信息辅助AMCL算法重定位,提高了定位算法的鲁棒性。在仿真实验场景下对该算法进行了实验,结果表明,在变电站室内外切换场景下,该算法可以获得稳定连续的定位数据,其均方根误差相比GPS/IMU与AMCL单独定位分别降低了63.4%和54.9%,机器人重定位时间相比原算法降低了47.1%。

无人化仓库下异构机器人混合任务分配研究

在具有若干个障碍区的码头无人化仓库中,为解决异构机器人系统对混合任务的有效分配问题,文中提出一种模糊聚类融合的扩展一致性束算法。在采用模糊聚类划分任务子区域和利用时间窗设置混合任务执行顺序的基础上,提出机器人分组资源配置策略,以任务分配收益最大、运行时间最短为目标,建立异构机器人系统任务分配的数学模型,通过扩展一致性束算法,在各个子区域内完成任务分配。结果表明:扩展一致性束算法缩短了任务分配时间,得到各子区域内机器人的执行任务序列并且每架机器人所分配到的任务数保持均衡。

智能变电站巡检机器人路径规划的改进ABC算法及其应用研究

为提升智能变电站巡检机器人的路径规划的效率,针对传统人工蜂群算法(ABC)的缺点,通过反向学习策略改进初始种群,利用精英反向学习优化算法的时间滞后性,同时借助差分算法的变异思维改进蜜源更新环节,提高算法的深度挖掘性能和全局寻优性能。实验数据表明,改进的ABC算法能够有效降低73.3%的巡检路径规划时间,巡检准确率可达95.2%,该算法可以提高智能变电站巡检机器人路径规划的效率,对提升智能变电站巡检机器人的智能化水平具有积极影响。

基于时空网络的变电站巡检机器人视觉导航避障研究

为提升变电站巡检机器人视觉导航避障效果,将卷积神经网络与循环神经网络相结合,提出一种轻量级时空网络结构。网络以机器人道路场景视频帧为输入,分别从空间域和时域2个维度对可行道路区域特征进行分析挖掘。针对空间域特征,网络先采用多种图像增强技术来丰富道路特征信息,再利用高效率卷积单元、残差连接以及注意力机制等模块构建卷积网络结构,由浅到深提取可行道路空间位置特征。对于时域特征,网络在空间特征基础上引入基于卷积计算的长短期记忆循环网络,保障时序特征提取的同时避免空间特征被破坏,并结合自注意力结构提升网络对关键信息的聚焦度,降低噪声数据干扰。根据所提时空域特征,设计分类回归预测结构,分别对机器人行驶方向及对应偏转角度进行预测,提升机器人导航避障效果。最后,考虑到实际变电站机器人巡检场景的高度相似性,设计特征差分模块来减少对冗余特征重复计算,保障实际应用效率。多个数据集上的实验结果表明:所提方法可以有效提取道路场景信息的时空特征并准确预测机器人下一步动作;与同类型方法相比,该方法具有更高的鲁棒性,可以更高效智能地实现导航避障。

多机器人系统感知能力和控制体系结构综述

为了促进多机器人系统(multi robot system,MRS)的智能化、无人化发展,并提升MRS在不同工作环境中的探测能力和系统的灵活性,本文从MRS的感知能力及其控制系统架构的角度出发,深度调研并分析了MRS相关的研究与工作,重点探讨了空中、地面、水面、水下4种应用环境下的MRS感知能力与控制系统架构,并对未来的研究方向进行展望。本文的结果可对于后续MRS在感知方法和控制系统的选用上提供参考。

面向变电站机器人巡检的加权嵌套决策树数据质量协同评价方法

针对现有数据质量评价存在完成主体单一、方法主观性强等问题,提出面向变电站机器人巡检的加权嵌套决策树数据质量协同评价方法。首先,构建一种变电站机器人巡检数据质量的协同评价框架;然后,构建包含数据及时性、数据完整性、数据准确性和数据重复性4个指标及其评价规则的指标体系,并据此建立基于加权嵌套决策树的数据质量评价模型;最后,通过某变电站巡检机器人A的巡检数据验证所提方法的有效性和优越性。案例分析表明,所提方法的评价结果不仅与专家评议结果一致且优于加权决策树的评价结果,所提协同评价框架有助于实现巡检数据质量的实时评价。

粮食收购智能扦样系统设计与研究

针对粮食收购扦样环节存在的劳动强度大、过度依赖人工、智能化程度低等问题,研发出一种能用于粮食行业车载散料或袋装的各类粮种的全自动、智能快速扦样系统。系统以机器人技术为载体,结合自动控制技术、图像识别技术、信息技术等,能够完成车辆信息识别、车厢尺寸及位置识别、自动扦样、智能缩分、自动输送、余粮回车、自动清理等。连续扦样时,粮食扦样分样时间约7 min/次。系统可对粮食入仓进行闭环控制,实现粮食入仓智能扦分无人化、标准化,消除人为因素干扰,杜绝扦样环节作弊现象。

四足巡检机器人最优避障路径生成系统研究

变电站巡检环境非常复杂,使得巡检机器人很难以最快的速度找到最优避障路径。为解决该问题,设计了变电站轻量化四足巡检机器人最优避障路径生成系统。搭建机器人最优避障路径生成系统架构和逻辑框架。系统硬件以MSP430为核心,主要由主控制模块、传感器模块、运动控制模块、计算机远程管理模块和无线通信模块组成。在系统硬件支持下,机器人操作系统(ROS)操作框架的各模块间通过节点耦合连接,以保证路径规划和最优路径生成效率与质量。在ROS操作框架基础上,A~*算法通过遍历周边环境地图所有节点,选择与生成变电站轻量化四足巡检机器人最优避障路径。试验结果表明,所提系统生成的避障路径为最优避障路径,并且偏航角较小、生成耗时较短。该系统可为机器人避障规划领域研究提供参考。

面向无人作业的天空地协同网络:需求、挑战、技术变革机遇

在偏远、危险地区,机器人可感知环境、智能交互,协同完成复杂任务。以卫星和无人机为主体的天空地协同网络能够为这些机器人提供全域泛在、随遇接入的通信服务。首先,分析无人作业发展趋势和机器人通信需求。基于此,面向机器人通信的特点,建议跳出“信息传输管道”的传统视角,在支持信息传输的同时,关注信息的内容和价值。进一步综合考虑机器人通信中信息生成的动作及其反馈,提出潜在技术变革的切入点。具体地,从结构化通信资源配置、机器人行为调控和感-传-算-控闭环模型三个方面阐述维纳控制论启发的通信范式变革途径。

复杂海洋环境下无人船仿真教学平台设计

针对机器人工程专业在移动机器人控制领域的理论与实践相结合的教学需求,利用机器人操作系统和Gazebo物理仿真引擎以及USVSim仿真平台,开发复杂海洋环境下无人船仿真教学平台。该平台实现了无人船的模型搭建、海洋环境扰动模拟、模型动力学参数辨识以及控制算法验证等功能。通过无人船仿真场景实验,表明了该仿真教学平台的可靠性与有效性,可弥补实验教学的不足,培养学生应对现实工程挑战的能力。