A novel explosion-proof walking system: Twin dual-motor drive tracked units for coal mine rescue robots

A new explosion-proof walking system was designed for the coal mine rescue robot(CMRR) by optimizing the mechanical structure and control algorithm. The mechanical structure innovation lies mainly in the dual-motor drive tracked unit used, which showed high dynamic performance compared with the conventional tracked unit. The control algorithm, developed based on decision trees and neural networking, facilitates autonomous switching between "Velocity-driven Mode" and "Torquedriven Mode". To verify the feasibility and effectiveness of the control strategy, we built a self-designed test platform and used it to debug the control program; we then made a robot prototype and conducted further experiments on single-step, ramp, and rubble terrains. The results show that the proposed walking system has excellent dynamic performance and the control strategy is very efficient, suggesting that a robot with this type of explosion-proof walking system can be successfully applied in Chinese coal mines.

Development of two rescue robots for disaster relief operations in narrow debris

This paper proposes two novel rescue robots,including a cutter robot and a jack robot,which are aimed to contribute to rescue activities such as to cut through obstacles and to jack up debris in dangerous sites and narrow spaces,where a rescue team can not work or approach.Firstly,a multilinked tracked rescue robot platform composed of connected crawler vehicles is developed,which has high mobility on irregular terrain and ability to move into narrow collapsed structures.Then,the cutter robot and jack robot are designed on the basis of rescue robot platform equipped with a cutter or a jack mechanism and corresponding manipulators in the front segment.The cutter refitted by an angle grinder is able to cut through 10 mm diameter steel bars.The electric jack mechanism designed based on multiple layers screw sleeves structure can lift up 300 kg load from 70 mm to 400 mm.Experimental results validate the capability of the two rescue robots.

DEVELOPMENT OF A SHAPE-SHIFTING MOBILE ROBOT FOR URBAN SEARCH AND RESCUE

A portable shape-shifting mobile robot system named as Amoeba Ⅱ（A-Ⅱ） is developed for the urban search and rescue application. It is designed with three degrees of freedom and two tracked drive systems. This robot consists of two modular mobile units and a joint unit. The mobile unit is a tracked mechanism to enforce the propulsion of robot. And the joint unit can transform the robot shape to get high environment adaptation. A-Ⅱ robot can not only adapt to the environment but also change its body shape according to the locus space. It behaves two work states including the linear state （named as I state） and the parallel state （named as Ⅱ state）. With the linear state the robot can climb upstairs and go through narrow space such as the pipe, cave, etc. The parallel state enables the robot with high mobility on rough ground. Also, the joint unit can propel the robot to roll in sidewise direction. Two modular A-Ⅱ robots can be connected through jointing common interfaces on the joint unit to compose a stronger shape-shifting robot, which can transform the body into four wheels-driven vehicle. The experimental results validate the adaptation and mobility of A-Ⅱ robot.

Mobile platform of rocker-type coal mine rescue robot

After a coal mine disaster,especially a gas and coal dust explosion,the space-restricted and unstructured underground terrain and explosive gas require coal mine rescue robots with good obstacle-surmounting performance and explosion-proof capability. For this type of environment,we designed a mobile platform for a rocker-type coal mine rescue robot with four independent drive wheels.The composition and operational principles of the mobile platform are introduced,we discuss the flameproof design of the rocker assembly,as well as the operational principles and mechanical structure of the bevel gear differential and the main parameters are provided.Motion simulation of the differential function and condition of the robot running on virtual,uneven terrain is carried out with ADAMS.The simulation results show that the differential device can maintain the main body of the robot at an average angle between two rockers.The robot model has good operating performance.Experiments on terrain adaptability and surmounting obstacle performance of the robot prototype have been carried out.The results indicate that the prototype has good terrain adaptability and strong obstacle-surmounting performance.

CAN-based Control System Design on Minor-caliber Deep Well Rescue Robot

By introducing a small-caliber deep well rescue robot,a hold-hug pattern rescue mechanism was brought forward.In order to reduce the volume,the under-well rescue mechanism is modularizing designed.At the same time,the audio and video systems,the illumination system and the ventilation system are expatiated.The rescuing robot can rescue the falling person in the deep well,it can save much manpower,material resources and time.It’s really an ideal rescue device for the small-caliber fall.

A Wireless Communication Method with Dynamic Adding Nodes for the Underground Search and Rescue Robot

有为地下的搜索和营救机器人的动态增加的节点的一个无线通讯方法被建议：修理控制器的地址，动态地增加 repeater 节点进网络，并且转移活动终端的地址。与这个方法，搜索和营救机器人能到达一个矿的更深的地方帮助在一条单个隧道通过无线通讯与控制器救并且保持联系，甚至在收音机波浪不能通过厚墙的一个复杂巷道。在在单个隧道的双向多跳跃通讯的过程的碰撞将被通讯方向优先级和反应信号机制也解决，到提高通讯的可靠性。最后，一件样品被设计，一个实验被进行验证方法的效率。

The theoretical research on localization using improved particle filter for mine rescue robot in unknown underground space

The localization for mine rescue robot in unknown space of coal mine emer- gency was researched,basing on the requirement of mine rescue robot localization which enters the scene of the coal mine accident,unknown circumstance,the unstructured, non-Gaussian and nonlinear work-space for robot works.The localization using particle filter was proposed to which is applied in mine rescue robot in unknown under-ground space.Meanwhile,focusing on severe particle sample degeneracy in the primary particle filter,an improved particle filter was proposed to reinforce the stability of particle filter.Be- ing compared with localization using extended Kalman filter through simulation experiment the localization using particle filter is proved to have more locating accuracy in unknown underground space and better computational real-time ability,which solves the pre-local- ization problem of robot underground.

Human Detection by Robotic Urban Search and Rescue Using Image Processing and Neural Networks

This paper proposes a new approach for detecting human survivors in destructed environments using an autonomous robot. The proposed system uses a passive infrared sensor to detect the existence of living humans and a low-cost camera to acquire snapshots of the scene. The images are fed into a feed-forward neural network, trained to detect the existence of a human body or part of it within an obstructed environment. This approach requires a relatively small number of images to be acquired and processed during the rescue operation, which considerably reduces the cost of image processing, data transmission, and power consumption. The results of the conducted experiments demonstrated that this system has the potential to achieve high performance in detecting living humans in obstructed environments relatively quickly and cost-effectively. The detection accuracy ranged between 79% and 91% depending on a number of factors such as the body position, the light intensity, and the relative color matching between the body and the surrounding environment.

An Improved Iterated Greedy Algorithm for Solving Rescue Robot Path Planning Problem with Limited Survival Time

Effective path planning is crucial for mobile robots to quickly reach rescue destination and complete rescue tasks in a post-disaster scenario.In this study,we investigated the post-disaster rescue path planning problem and modeled this problem as a variant of the travel salesman problem(TSP)with life-strength constraints.To address this problem,we proposed an improved iterated greedy(IIG)algorithm.First,a push-forward insertion heuristic(PFIH)strategy was employed to generate a high-quality initial solution.Second,a greedy-based insertion strategy was designed and used in the destruction-construction stage to increase the algorithm’s exploration ability.Furthermore,three problem-specific swap operators were developed to improve the algorithm’s exploitation ability.Additionally,an improved simulated annealing(SA)strategy was used as an acceptance criterion to effectively prevent the algorithm from falling into local optima.To verify the effectiveness of the proposed algorithm,the Solomon dataset was extended to generate 27 instances for simulation.Finally,the proposed IIG was compared with five state-of-the-art algorithms.The parameter analysiswas conducted using the design of experiments(DOE)Taguchi method,and the effectiveness analysis of each component has been verified one by one.Simulation results indicate that IIGoutperforms the compared algorithms in terms of the number of rescue survivors and convergence speed,proving the effectiveness of the proposed algorithm.

基于救援机器人的人体关节点检测方法

为了使救援机器人在危楼环境下能够精确地检测人体关节点,以代替救援人员进入危险现场,提出了一种基于救援机器人的人体关节点检测方法。首先,通过Kinect相机获取人体关节点检测数据,采用归一化的方法对关节点数据进行平滑预处理。其次,对预处理数据加入人体关节长度约束和关节旋转角约束,从而生成每个人体关节点空间位置。最后,采用Tsai方法进行手眼标定,得到机械臂和伤员之间的距离。实验结果表明该方法在危楼救援环境下能够准确测量伤员关节点位置,验证了所提出检测方法的有效性。

基于机器视觉的救援机器人自动避障技术研究

针对矿山救援机器人易受粉尘、光线昏暗等因素影响,导致其自动避障能力下降问题,研究一种基于机器视觉的救援机器人自动避障策略,可以实现在复杂环境下的有效避障。设计一种基于改进非局部均值滤波和多尺度B样条小波变换的机器视觉算法,以获得更高质量图像并精确获得障碍物边缘,确保救援机器人自主识别并避开障碍物。仿真结果表明:该算法相比传统算法在图像降噪和边缘检测上均体现出优越性。

面向溺水救援机器人平稳跟踪的模糊比例微分控制视觉伺服方案

针对溺水救援机器人的平稳跟踪需求,提出一种基于模糊比例微分控制的视觉伺服方案,通过场馆顶部安装的俯视摄像头获取机器人的坐标位置,使用虚拟导航线设计动态行走路径,计算偏移方向、偏移角并制定转弯规则;利用三角隶属度函数制定模糊比例、微分控制规则表,根据2种规则表中的比例、微分系数分别控制机器人的偏移角、距离偏移量及其变化率,实现机器人的跟踪与避障的平稳性调整;机器人采用核相关滤波跟踪算法对溺水人员进行跟踪,在溺水人员位置变化时调整运动方向,依靠实时、稳定的声呐信息设置偏移角,实现避障功能;对所提出的方案在先锋P3DX型机器人上进行实验验证。结果表明:机器人能及时应对目标变化,没有跟错、跟丢现象;在不同工况时的横滚角均小于1°,避障率达到100%,能够快速、稳定、准确地到达目标位置,达到溺水救援机器人的前期应用要求。

煤矿机器人技术产业痛点及智能化分级标准

探讨了我国煤矿机器人行业的发展现状、痛点以及未来趋势。在“机器人+”大时代背景下,从机器人企业数量、地域分布、产业园区建设、优势赛道、国家政策等层面阐述了我国机器人产业发展情况,并阐述国内互联网和制造业大厂入局机器人带来的变革与挑战;重点分析了煤矿机器人技术及产业痛点,指出了煤矿机器人实现智能化应具备的3大能力;提出了应加强其供应链、标准体系等方面建设;详细介绍了煤矿机器人L_(0)~L_(5)的分级标准。

仿蜥蜴肌腱牵引的矿用搜救机器人眼研究

针对井下环境复杂、巷道狭窄以及目前搜救机器人普遍存在的探测角度小、响应速度慢等问题,模仿蜥蜴眼肌腱牵引的生理结构设计矿用搜救机器人仿生眼。采用STM32单片机和蓝牙通讯技术控制仿生眼的运动,在远程终端上实时显示仿生眼捕捉到的视觉信息。模型仿真及样机测试结果表明,所设计的八自由度矿用搜救机器人仿生眼视觉系统,具备俯仰、偏航、滚动三转动自由度的360°全方位搜寻能力,其角速度能够满足快速性的要求,有效实现了搜救机器人视觉系统视角大、响应快、独立性强等特点,提高了搜寻效率和范围。

履带式救援平台机动性能仿真分析

为了能够有效克服复杂非结构环境,尽快到达自然灾害救援现场开展救援,要求履带式救援平台具备良好的越野机动性和通行能力,因此,在装备设计阶段,必须要对履带式救援平台的机动性和通过性指标进行验证。文中采用理论计算和多体动力学仿真分析相结合的方法,开展了履带救援平台最高速度、最大爬坡度、越壕宽度、越障高度等机动性和通过性指标的校核和仿真验证,结果表明提出的指标均能得到满足。仿真计算过程还得到了车辆运动姿态和载荷的变化趋势,为进一步优化履带救援平台推进系统的方案设计提供了支撑。

基于改进A^(*)算法的矿用机器人救援路径规划及仿真分析

【目的】煤矿井下灾后现场情况复杂,针对传统A^(*)算法的煤矿机器人救援路径规划存在路径不安全、效率低等问题,结合栅格地图及救援机器人可沿任意方向移动的特点,多方面对传统A^(*)算法进行改进。【方法】首先,引入了机器人尺寸叠加到障碍物的概念,以确保路径的安全性。其次,通过优化启发函数,降低偏离最佳路径节点的扩展数量,减少冗余节点与路径转折,降低了计算复杂度。最后,采用动态调整算法将路径转折角圆弧化,对所得路径平滑处理,提高了路径的可操作性。最终获得路径代价更小、耗时更短、转弯次数更少的优化路径。基于改进的A^(*)算法,利用MATLAB开展了不同尺寸及不同障碍物覆盖率下救援机器人路径规划的仿真模拟试验。【结果】结果表明:相较于传统A^(*)算法,在崎岖环境地图中改进的A^(*)算法使搜索节点降低了26.51%、计算时长减少了80.42%、路径长度缩短了31.85%、转向次数减少了44.44%,提高了路径的搜索效率和平滑程度。【结论】改进的A^(*)算法为复杂工况环境下煤矿机器人的救援工作提供了一定的理论基础。

基于改进A*和势场法的轮式煤矿救援机器人路径规划

煤矿救援机器人在非结构化井下巷道环境中执行搜救任务,传统的路径规划算法用于搜索空间较大或者复杂度较高的非结构化环境时,可能会面临效率低、非最优路径和平滑度较差等问题;此外,巷道存在复杂的交叉口等环境特征,机器人在该区域容易偏离预设路线或与路口壁面发生剐蹭。为了克服这些问题并提高机器人的导航精度,提出了针对轮式煤矿救援机器人的路径规划算法改进方案:①改进启发式全局路径规划A*算法,通过分层邻域搜索与剪枝的方法改进邻域搜索方式,优化代价函数以更好地平衡实际代价和启发式代价的影响,更准确地评估每个节点的代价,使其适应实际情况且缩减了计算量,并利用B样条方法对路径进行平滑处理;②利用随机样本一致算法(RANSAC)构建煤矿巷道壁面的几何模型,以便提取交叉路口特征点坐标纳入规划系统,利用B样条曲线基函数的局部支撑性优化路径,当后续添加路径优化点时,仅影响相应区间的曲线形状,对路径的其余部分不产生影响;③根据构建的环境几何模型和提取的特征点建立综合局部势场,引入调整系数优化势场分布,并使用粒子群算法(PSO)优化的PID算法实现运动控制,增强机器人针对巷道交叉口等复杂环境通行的适应能力。通过MATLAB和机器人操作系统(ROS)仿真验证了算法原理与应用的可行性,结果表明该方法可以实现在复杂交叉环境中路径规划、自主行驶等功能。

轮履式救援机器人结构设计

轮履式救援机器人是一种在紧急救援和灾害应对中发挥关键作用的机器人系统。本文旨在探讨轮履式救援机器人的结构设计,以提高其在复杂环境下的性能和适应性。本文提出了一种具有灵活机动性和高稳定性的轮履式救援机器人设计方案。其原理是采用双履带爬行机器人,经过调节履带角度,实现机器人自由移动,从而达到翻越屏障的目的,并且依靠带有摄像头的机械手臂实现多方位探测巡逻。运用SolidWorks软件对轮履式救援机器人的三维进行模拟装配,验证本论文方案设计的可行性。通过结构设计、材料选择和自主性控制的综合考虑,可以使这类机器人更加适应各种复杂环境,提高救援效能。

深井救援机械设备的结构设计与研究

旨在制造一个应用于深水井救援领域的救援机器人,以弥补该领域内专业救援设备的空白。该机器人由驱动模块、侦查模块、动力模块和救援模块4个模块组成。其体积小,活动灵活,能在狭窄的井中进行多种操作,完成在狭窄空间内人所不可能或很难完成的任务。在使用本装置实施救援时,只需在地面上进行远程控制便能快速完成救援任务。

基于BP-PID的应急救援机器人步进电机控制算法研究

应急救援机器人的应用能够有效提高应急救援能力,电机作为机器人的核心驱动装置,其控制精度的高低将直接影响机器人性能的优劣。设计BP-PID步进电机控制系统,运用MATLAB/Simulink软件仿真。结果表明,相比于PID控制,BP-PID控制超调量更小、调节时间更短,控制效果更好。