A Study on Development of a Hybrid Aerial/Terrestrial Robot System for Avoiding Ground Obstacles by Flight

To date, many studies related to robots have been performed around the world. Many of these studies have assumed operation at locations where entry is difficult, such as disaster sites, and have focused on various terrestrial robots, such as snake-like, humanoid, spider-type, and wheeled units. Another area of active research in recent years has been aerial robots with small helicopters for operation indoors and outdoors. However,less research has been performed on robots that operate both on the ground and in the air. Accordingly, in this paper, we propose a hybrid aerial/terrestrial robot system. The proposed robot system was developed by equipping a quadcopter with a mechanism for ground movement. It does not use power dedicated to ground movement, and instead uses the flight mechanism of the quadcopter to achieve ground movement as well. Furthermore, we addressed the issue of obstacle avoidance as part of studies on autonomous control. Thus, we found that autonomous control of ground movement and flight was possible for the hybrid aerial/terrestrial robot system, as was autonomous obstacle avoidance by flight when an obstacle appeared during ground movement.

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.

基于Robot Framework测试框架的机载娱乐系统自动化测试设计

在对机载娱乐系统软件架构进行分析的基础上,阐明了机载娱乐系统自动化测试的必要性,设计了基于Robot Fra-mework测试框架的自动化分层测试组织结构,明确了自动化测试中测试用例、测试规程、测试结果之间的追踪性,并将设计的测试组织结构在实际项目中进行了应用。实践表明,采用所设计的自动化分层测试组织结构可以较好的满足机载娱乐系统在软件测试过程中的脚本维护、扩展、稳定测试等要求,有利于软件的快速交付。

基于奇异摄动分解的带机械臂旋翼无人机飞行稳定性研究

为了降低无人机和机械臂之间的耦合作用,提高带臂四旋翼无人机飞行过程中的稳定性,首先建立系统动力学模型,然后根据实际情况,对模型进行简化。在此基础上进行内、外环分解,外环为四旋翼位置控制和机械臂角度控制,内环为四旋翼俯仰角控制。对于外环的动力学模型,根据速度变化特点,利用奇异摄动理论对外环变量,即四旋翼线速度和机械臂角速度,进行快、慢变子系统分解,再次降低了系统间的耦合性。对于分解后的快、慢变子系统,设计非奇异终端滑模控制并引入干扰观测器,以期提高带臂四旋翼无人机飞行过程中的稳定性。最后,仿真验证了所设计算法的优越性。

基于模糊PID的球形两栖机器人的设计及控制

为了解决移动机器人对工作环境要求严格的问题,设计了一种适用于多变、狭窄环境的轻小型球形陆空两栖机器人,具有地面滚动和空中飞行两种运动模式,可以自主完成运动模式的切换。首先,设计了机器人的结构,包括滚动部分、飞行部分和模式切换部分。基于拉格朗日方法,建立了不同运动模式下的动力学模型,建立了基于欧拉方程的运动学模型。最后,根据机器人的运动模型,设计了飞行模式和地面滚动模式下的姿态控制器,并对控制器进行了仿真对比实验。在实机上进行了测试,实验结果表明,该机器人能够实现自主模式切换,在不同运动模式下运动稳定、姿态可控,在纯地面模式下具有一定的越障能力。在结构、控制方法及控制策略切换方法上对陆空两栖可变形机器人具有一定借鉴作用。

蝴蝶飞行机理及仿蝴蝶扑翼飞行器研究进展综述

仿生扑翼飞行器具有高机动性、高隐蔽性以及高效率等突出优势,在军事侦查、探险搜救等领域具有较好的应用前景,而其应用的基础是对生物飞行机理的深入探究.随着先进运动观测和实验技术的引入,对昆虫飞行行为的记录和分析更为便捷和准确.研究表明常见的昆虫拍打频率较高,在25~400 Hz之间,而蝴蝶较为特殊,其扑打频率较低,大约为10 Hz,对于蝴蝶的许多独特的飞行技能尚缺少足够的认识.蝴蝶前翼和后翼的翼面积都较大,身体同侧的前后翼几乎为同步拍打,且扑打幅度较大,甚至接近180°.蝴蝶飞行中身体有较大幅度的上下和俯仰震荡,翼和身体运动高度耦合.即便如此,蝴蝶仍具有敏捷的飞行能力,可以达到点对点的飞行目标,甚至上千公里的长途迁徙,是优秀的仿生学研究对象.因此,蝴蝶启发的仿生扑翼飞行器也得到了全世界研究人员的关注.蝴蝶的飞行机制相对于其他昆虫更加特殊,飞行行为和气动特性更为复杂,这使得仿蝴蝶扑翼飞行器的研制更加困难.目前对于仿蝴蝶飞行器的研制大多数对蝴蝶翼–身耦合的机理进行了简化,很少能实现受控的稳定飞行.最后,本文梳理了真实蝴蝶的飞行行为特点和飞行机理,指出了仿蝴蝶扑翼飞行器研制的关键技术,总结了该类飞行器未来的发展方向和应用前景.

基于IFWA⁃CS算法融合的移动机器人路径规划

为解决基本烟花算法(FWA)在移动机器人路径规划中存在收敛速度慢、易陷入局部最优等不足,首先将RRT算法与FWA算法结合以提升算法初始速度;其次,针对FWA算法存在收敛速度慢的问题,在其选择操作中采用精英选择与轮盘赌法相结合的选择机制增强算法的局部搜索能力;最后利用自适应莱维飞行策略改善其易陷入局部问题。仿真实验结果表明,融合算法的路径长度和收敛速度均得以提升,在移动机器人路径规划中具有很好的实用性。

Computer Vision-based Navigation and Predefined Track Following Control of a Small Robotic Airship

为小机器的飞艇，飞艇应该能够跟随一条预定义的轨道，这被要求。在这份报纸，计算机为机器的飞艇的基于视觉的航行和最佳的模糊控制策略被建议。第一，视觉航行基于环境的自然里程碑被介绍。例如，当飞艇在一个城市上正在飞时，大楼能被用作其几何性质从数字地图或一个地理信息系统(GIS ) 被知道的视觉烽火。然后，几何方法论被采用关于飞艇的取向和位置提取信息。以便在一个预定义的磁道上保留飞艇，一个模糊飞行控制系统被设计，它把那些数据用作它的输入。并且基因算法(气体) ，一个通用全球优化方法，被利用优化模糊控制器的会员功能。最后，航行和控制策略被验证。

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.

融合粒子群算法与改进灰狼算法的机器人路径规划

针对灰狼算法在处理机器人路径规划问题时存在路径较长、收敛速度较慢等问题,提出一种基于PSO与改进GWO的粒子群-灰狼混合算法(PSO-GWO)。通过多次运行PSO算法来确定初始狼群规模及初始适应度值;引入非线性收敛因子平衡GWO算法的探索和开发能力,提出动态惯性权重因子来保证头狼领导制度及促进种群交流;运用莱维飞行和贪婪策略使算法有效避免局部最优,获得最优解。仿真结果表明:该算法相较于GWO算法在3种地图下平均路径长度缩短17%、16%、16.2%;平均运行时间缩短13%、8%、16%。

基于改进乌燕鸥算法的移动机器人路径规划

为克服传统智能算法在解决复杂环境下移动机器人路径规划问题中存在的搜索效率慢和寻优精度低等不足,提出改进乌燕鸥优化算法(ISTOA)。以乌燕鸥算法(STOA)为基础,引入Circle混沌映射机制保证初始种群的质量,提升算法初期搜索效率。同时,提出旋转式翻筋斗搜索策略,对算法的扑食位置进行更新,提高了算法的局部寻优能力。在迁徙过程中,混合正弦控制非碰撞因子和自适应Lévy飞行策略平衡了算法的全局搜索和局部搜索。通过3种不同环境下移动机器人路径规划案例验证了改进乌燕鸥优化算法的有效性。结果表明:改进乌燕鸥优化算法可快速且稳定获得全局最优路径,整体寻优能力优于其他算法,有效地解决了移动机器人在复杂环境中的最优路径规划问题。

基于ROS和Pixhawk飞控自驾仪的无人清扫船研究

本研究旨在探索基于机器人操作系统(Robot Operating System,ROS)和Pixhawk飞控自驾仪的无人清扫船的应用。通过结合先进的自动化技术和海洋保护需求,设计了一种全新的无人船系统,旨在提高海洋环境清洁和生物多样性的保护效率。研究采用了遥感和机器视觉技术,实现了船只自主导航和集中式监测控制。实验结果表明,该无人清扫船系统具有良好的性能和可控性,为实现海洋保护目标提供了新的解决方案。

基于特征运动观测的蝴蝶前飞规律及样机验证

为了研究蝴蝶扑翼飞行的原理,研制低频扑翼的仿生器,通过蝴蝶飞行运动的生物学观测,提出蝴蝶的3种特征运动状态,分析扑翼运动、胸部俯仰运动及腹部摆动运动之间的相位关系,构建蝴蝶前飞运动学模型。基于“杆-膜”仿生翼的新工艺和定制的机载飞控系统,研制轻量化的仿生蝴蝶扑翼飞行器样机,研究蝴蝶样机的飞行控制策略。通过六维力传感器对样机做地面动力学测试,利用高速摄像机对样机飞行进行运动学跟踪,证明了基于特征运动状态的蝴蝶前飞规律和原理样机研制的有效性。

直升机人机协同控制方法研究与飞行验证

人机协同系统可以充分发挥人类智慧的优越性和机器人作业的高精度与高效率,被广泛应用于决策指挥、工业控制和医疗手术等领域。飞行员驾驶飞行器时需要实时处理大量信息并给出精准操控,操纵负担大。基于典型单旋翼直升机的操控特点,设计一种直升机协同驾驶机器人系统,驾驶机器人连接直升机周期变距杆控制直升机的俯仰运动和滚转运动,飞行员通过总距杆和脚蹬控制直升机的航向运动和升降运动。协同驾驶机器人可以在不改装原有直升机的基础上实现一种新型的人机协同飞行控制,快速提升现有直升机的自动化水平和飞行员在应急情况下的生存能力。研究驾驶机器人控制系统模型,建立适用于直升机人机协同控制的飞行模拟平台,通过飞行员在环飞行仿真初步验证了人机协同控制方法的可行性。在飞行仿真验证的基础上研制了驾驶机器人样机,并将样机搭载在SVH-4直升机上完成飞行实验验证。

Autonomous Formation Flight Control of Large-Sized Flapping-Wing Flying Robots Based on Leader–Follower Strategy

Birds in nature exhibit excellent long-distance flight capabilities through formation flight,which could reduce energy consumption and improve flight efficiency.Inspired by the biological habits of birds,this paper proposes an autonomous formation flight control method for Large-sized Flapping-Wing Flying Robots(LFWFRs),which can enhance their search range and flight efficiency.First,the kinematics model for LFWFRs is established.Then,an autonomous flight controller based on this model is designed,which has multiple flight control modes,including attitude stabilization,course keeping,hovering,and so on.Second,a formation flight control method is proposed based on the leader–follower strategy and periodic characteristics of flapping-wing flight.The up and down fluctuation of the fuselage of each LFWFR during wing flapping is considered in the control algorithm to keep the relative distance,which overcomes the trajectory divergence caused by sensor delay and fuselage fluctuation.Third,typical formation flight modes are realized,including straight formation,circular formation,and switching formation.Finally,the outdoor formation flight experiment is carried out,and the proposed autonomous formation flight control method is verified in real environment.

改进沙猫群优化算法的机器人路径规划

为了寻找更优的机器人移动路径,将沙猫群优化算法与三次样条插值方法进行融合,对沙猫群优化算法进行改进。在改进的沙猫群优化算法中,利用混沌映射的均匀性初始化种群以提高种群多样性;通过融合互利共生和莱维飞行策略减少局部最优解的消极影响,提高算法的收敛速度和精度。通过两种仿真实验对比6种优化算法的实验数据,结果表明,改进的沙猫群优化算法的最优解、最差解和平均解都优于对比算法,验证了改进沙猫群优化算法对于解决移动机器人路径规划问题的有效性和工程实用性。

Autonomous flight control with different strategies applied during the complete flight cycle for flapping-wing flying robots

Flapping-wing flying robots(FWFRs),especially large-scale robots,have unique advantages in flight efficiency,load capacity,and bionic hiding.Therefore,they have significant potential in environmental detection,disaster rescue,and anti-terrorism explosion monitoring.However,at present,most FWFRs are operated manually.Some have a certain autonomous ability limited to the cruise stage but not the complete flight cycle.These factors make an FWFR unable to give full play to the advantages of flapping-wing flight to perform autonomous flight tasks.This paper proposed an autonomous flight control method for FWFRs covering the complete process,including the takeoff,cruise,and landing stages.First,the flight characteristics of the mechanical structure of the robot are analyzed.Then,dedicated control strategies are designed following the different control requirements of the defined stages.Furthermore,a hybrid control law is presented by combining different control strategies and objectives.Finally,the proposed method and system are validated through outdoor flight experiments of the HIT-Hawk with a wingspan of 2.3 m,in which the control algorithm is integrated with an onboard embedded controller.The experimental results show that this robot can fly autonomously during the complete flight cycle.The mean value and root mean square(RMS)of the control error are less than 0.8409 and 3.054 m,respectively,when it flies around a circle in an annular area with a radius of 25 m and a width of 10 m.

矢量共轴双旋翼无人机的设计与仿真研究

设计了一款新型的具有矢量定向机构的共轴双旋翼无人机。在Webots移动机器人仿真软件的环境下完成对矢量共轴双旋翼无人机的实体造型与动力学建模,基于ROS机器人操作系统编写了矢量共轴双旋翼无人机的飞控程序,引入了双目定位算法进行空间定位。通过仿真实验验证了矢量共轴双旋翼无人机机构、飞控程序和双目定位算法的可行性,对快速开发新型无人机飞控和接入新型传感器有参考价值。

用于移动机器人路径规划的增强型蛇优化算法

针对蛇优化(SO)算法在路径规划过程中存在搜索效率比较低、收敛速度慢且寻优精度低等问题,提出了一种改进的蛇优化算法(GLSOA)。在全局勘探阶段采用莱维飞行扰动策略,以扩大算法搜索范围并丰富其种群多样性。同时,使用非线性收敛因子调节环境温度变化,以平衡算法的全局探索和局部开发能力。然后,在局部搜索阶段引入局部混沌搜索策略,以扩大混沌空间的搜索范围,提高算法的局部开发能力。最后,采用黄金正弦机制指引种群位置更新,缩小搜索范围,提高算法收敛精度和速度。仿真结果表明,改进的算法有效缩短了路径规划长度,算法的性能有了显著性的提高。

仿生扑翼飞行机器人自主导航系统研究进展

仿生扑翼飞行机器人模仿自然界鸟类和昆虫等生物的飞行方式,具有安全性强、迷惑性好等优点,在灾害救援、反恐防暴等方面具有极其重要的应用前景。为实现其在未知复杂环境下的自主飞行并执行探测任务,需研制一套集感知建图、规划避障与飞控制导等功能模块为一体的导航系统。本文首先对扑翼飞行机器人的导航系统进行了概述,按照翼展大小将扑翼飞行机器人分为微小型和大中型两类,其次对比分析了国内外在微小型、大中型扑翼飞行机器人导航系统方面的主要研究进展。接着对自主导航系统所涉及到的感知定位与建图、运动规划与避障、轨迹跟踪与飞控制导等关键技术进行了分析总结,指出其局限性及亟待解决的问题。最后,对未来的研究趋势进行了展望,包括提升机载嵌入式计算能力、多模态信息融合、面向多模态飞行的流场感知、仿生视觉系统研究、群体感知与编队控制等热点方向。