A 6-DOF humanoid wall-climbing robot with flexible adsorption feet based on negative pressure suction

A wide range of dangerous and special tasks have witnessed the applications of wall-climbing robots, but they still cannot adapt well torough or sloping walls. This paper proposes a 6-DOF (degree of freedom) humanoid wall-climbing robot (HWCR) based on the principle of negative pressure suction. HWCR has the advantages of flexible adsorption feet, strong adaptability, strong anti-subversion performance, and high friction to the wall. We deduce mechanics formulas and carry out a parametric design of the foot structure so that it can meet the requirement of robot wall climbing. We use Fluent to analyze the flow field of the adsorption foot and determine the motor speed that can provide a reliable adsorption force. Using the D-H matrix to plan gait, we also design a compound cycloid-based foot trajectory to reduce the impact between the HWCR and the wall. Experiments on the uneven wall and sloping wall show that the vehicle can walk with an ideal gait, and the resistance value of the servo on each joint is much lower than the critical value, which ensures the smooth movement of the HWCR.     

Application of artificial neural network method to predict the breakage properties of PGE bearing chromite ore

In the present investigation, systematic grinding experiments were conducted in a laboratory ball mill to determine the breakage properties of low-grade PGE bearing chromite ore. The population balance modeling technique was used to study the breakage parameters such as primary breakage distribution (B_{i, j}) and the specific rates of breakage (S_i). The breakage and selection function values were determined for six feed sizes. The results stated that the breakage follows the first-order grinding kinetics for all the feed sizes. It was observed that the coarser feed sizes exhibit higher selection function values than the finer feed size. Further, an artificial neural network was used to predict breakage characteristics of low-grade PGE bearing chromite ore. The predicted results obtained from the neural network modeling were close to the experimental results with a correlation of determination R² = 0.99 for both product size and selection function.     

Shared human–robot path following control of an unmanned ground vehicle

This paper considers the shared path following control of an unmanned ground vehicle by a single person. A passive measure of human intent is used to blend the human and machine inputs in a mixed initiative approach. The blending law is combined with saturated super-twisting sliding mode speed and heading controllers, so that exogenous disturbances can be counteracted via equivalent control. It is proven that when the proposed blending law is used, the combined control signals from both the human and automatic controller respect the actuator magnitude constraints of the machine. To demonstrate the approach, shared control experiments are performed using an unmanned ground vehicle, which follows a lawn mower pattern shaped path.     

论携号转网行为的私法规制

以电信用户入网协议为切入点,电信用户的携号转网行为应受到《合同法》《消费者权益保护法》等私法规范的保护与限制。该行为引起的格式条款解释、合同终止、违约责任、损失赔偿等问题,不能仅靠《电信条例》等公法规范来调整。应当积极引导广大消费者用户以私法领域相关规定为依据,转变争议解决思维,拓宽纠纷处理途径,合理选择维权手段,以保护自身合法民事权益,与行业监管部门共同推动电信行业有序发展。     

基于旋翼负压混合吸附的爬壁清洗机器人系统动力学性能研究

针对爬壁清洗机器人越障时,负压装置的吸附力下降导致吸附不稳定的问题,设计了一种旋翼负压混合吸附工作的多边形履带清洗机器人,并对爬行稳定性及越障性能进行了动力学分析。首先根据机器人爬壁的运动原理,建立机器人沿玻璃幕墙上的动力学模型,计算出电机理论驱动力矩;其次分析机器人在跨越障碍过程中的运动模型,结合与壁面接触的实际受力状态,对越障过程中关键阶段的本体倾翻、滑移两种失效形式进行运动学和动力学分析;然后根据玻璃幕墙实际的障碍高度,确定多边形履带的参数和理论驱动力矩的大小,并研制了实验样机进行爬行和越障试验,结果表明所设计的机器人具有良好的越障性能。     

新型树启发式搜索算法的机器人路径规划

面对三维空间移动机器人从起始点到终止点的最短路径问题,提出一种新型的边缘点树启发式搜索(TreeEP)算法,该方法将地图空间进行密度可调的三维离散化处理,根据障碍安全距离筛选出障碍物的可靠边缘点信息,再利用树扩散架构选出最能引导搜索方向的潜力点进行扩散搜索,最终得出最短路径。提出局部调整策略,得到改进的Tree-EP算法。实验结果表明,在带障碍复杂地形最短路径搜索应用中,提出的Tree-EP算法与已有方法相比,能找到更短的移动路径。     

基于机器视觉的机车齿轮毂全自动双轴拧紧机的设计和应用

设计了基于机器视觉的机车齿轮毂全自动双轴拧紧机,根据拧紧工艺和扭矩控制原理实现对螺栓拧紧力矩的控制;通过丝杠变径机构,实现不同规格齿轮毂螺栓拧紧;利用机器视觉实现螺栓位置的识别以及初始位置的确定;讨论了自动拧紧机控制系统的硬件组成和软件系统配置,并介绍了防错、防漏功能的设计流程。螺栓自动拧紧机可提高装配精度和操作效率,降低工人的劳动强度。     

Plant inspection by using a ground vehicle and an aerial robot: lessons learned from plant disaster prevention challenge in world robot summit 2018

Abstract

In recent years, to prevent accidents and disaster are desired by implementing maintenance and management of facilities, such as conducting periodic inspections with appropriate frequency at plants. However, because the dangerous materials such as flammable gas and explosives is used in a plant, and there are many dangerous places in a plant such as high-temperature environment and high places and narrow spaces, it is desirable to use a remote-controlled robot for safety work and short inspections. Against this background, the Disaster Robotics Category-Plant Disaster Prevention Challenge was held in Japan at the World Robot Summit 2018. Our team was ranked 3rd in this competition, because our strategy of ‘inspection and investigation in cooperation with UGV and UAV’ was effective. In this paper, the competition contents of World Robot Summit 2018 and the robot inspection system that we are studying are explained. And what kind of strategy was challenged and result for these given competition tasks by using our robot system are introduced. And the lessons learned such as advantages and issues in UGV and UAV collaboration work at this competition are described for evaluate a robot investigation system for disaster response and inspection work at plants.     

公路治超必须从动态称重抓起

公路治超事业与动态称重事业是一对相互依存的共同体,治超离不开动态称重,动态称重也离不开治超事业。在"四个一流"公路治超体系建设的同时,与公路治超同呼吸共命运的动态称重技术也取得了很大发展,已经完成了由轴载荷计重模式向整车称重模式的转化,新技术已经具备高准确度、高稳定性、高通行率等特征,能够适应公路现场应用,计量结果完全不受车辆不规则驾驶的影响,精准可靠。公路治超事业需要准确的称重技术,动态称重技术需要公路治超的舞台,"四个一流"的公路治超信息化体系建设更离不开一流的动态称重技术。