仿人机器人运动规划研究进展

在分析仿人机器人运动规划特性的基础上,对仿人机器人运动规划涉及的路径规划和步态规划两大问题及其典型方法进行了阐述和分析.对基于博弈论思想的离线足迹规划和基于传感信息融合的在线滚动路径规划两种路径规划策略进行了剖析,同时对几何约束法、模糊逻辑法、神经网络法、遗传算法法、自然步态法等5种常用的离线步态规划方法和3类在线姿态调整及控制方法即基于动力学模型的方法、基于倒立摆模型的方法、不基于模型的方法的算法思想和实验应用进行了分析与评价.最后对仿人机器人运动规划评价方法和运动规划研究的发展进行了讨论.     

双工业机器人协调复杂作业实验研究

就双机器人搬运刚体之外的复杂作业提出了面向操作物的运动描述与规划方法，以及适应于工业机器人系统的基于关节位置控制的协调控制策略。在两工业机器人协调系统上实现了相关多轴孔装配，复杂工件边缘跟踪，弹性体操作与装配作业实验。     

冗余度机器人运动学容错性能同一性问题的研究

以退化条件数为容错性能指标,对两种结构的空间4R冗余度机器人进行了运动规划,同时考察了关节速度突变这一容错指标,分析了这两种不同结构的机器人的Denavit—Hartenberg参数和末端初始位置对这两个容错指标的影响;另外,利用ADAMS和PowerCube机器人进行仿真和实验,分析讨论了故障时刻关节速度突变对机器人关节力矩和末端操作精度的影响。研究结果表明,能使机器人退化条件数和关节速度突变这两个容错指标同时达到最优的结构特征是存在的;与其他尺寸参数相比,机器人各偏置的臂长比例关系对其容错性能的影响更为突出;机器人初始姿态对各容错指标同一性程度影响显著;在故障关节锁定时刻,机器人关节速度突变越大,其关节力矩突变越大,且末端操作误差越大。     

CT导航手术2T-3R并联机器人型综合研究

提出了CT导航手术并联机构选型的具体原则。采用基于位移子群的位移流形运动综合法对微创外科手术少自由度并联机器人进行了型综合。详细总结了位移流形基本理论和基于位移流形的型综合方法。基于高灵活性指标,构造了2T-3R少自由度并联机器人的11种基本流形及其24种子流形,推导得到了102种灵活性较高的2T-3R并联机构,确定了研究中所采用的具体结构,并分析了其性能特点。对其灵活性的初步分析表明,该并联机器人可以用于CT导航微创外科手术。     

基于多传感器融合信息的移动机器人速度控制方法

为提高移动机器人在复杂环境下的速度控制精度和适应能力,提出了一种基于多传感器融合信息的移动机器人速度控制方法.首先,根据多传感器非线性优化融合理论,通过最小化运动观测残差的方法来构建移动机器人运动状态优化估计模型.然后,对利用单目相机、轮式里程计及惯性测量单元(inertial measurement unit,IMU...     

基于多智能体的自重构机器人突现控制系统平台的构建

构建了基于多智能体的模块化自重构机器人系统实验平台.在详细分析了自重构系统的主要特点的基础上,设计了一种新型的同构阵列式模块化自重构机器人M-Cubes,阐述了多智能体分布式体系的控制结构,给出了实验平台的设计策略,包括单智能体结构设计、控制系统的硬件设计、单元模块的基本运动和系统运动规划策略.利用Ja-va3D开发了一个仿真试验平台,对各种控制算法进行了仿真和测试评估.     

2D to 3D Manipulation and Assembly of Microstructures Using Optothermally Generated Surface Bubble Microrobots

Hydrogel microstructures that encapsulate cells can be assembled into tissues and have broad applications in biology and medicine. However, 3D posture control for a single arbitrary microstructure remains a challenge. A novel 3D manipulation and assembly technique based on optothermally generated bubble robots is proposed. The generation, rate of growth, and motion of a microbubble robot can be controlled by modulating the power of a laser focused on the interface between the substrate and a fluid. In addition to 2D operations, bubble robots are able to perform 3D manipulations. The 3D properties of hydrogel microstructures are adjusted arbitrarily, and convex and concave structures with different heights are designed. Furthermore, annular micromodules are assembled into 3D constructs, including tubular and concentric constructs. A variety of hydrogel microstructures of different sizes and shapes are operated and assembled in both 2D and 3D conformations by bubble robots. The manipulation and assembly methods are simple, rapid, versatile, and can be used for fabricating tissue constructs.     

蛇形机器人水中上浮下潜运动仿真研究

根据水下环境特征,研究蛇形机器人在水中三维空间的运动步态.基于虚拟机器人实验平台(V-REP)动力学仿真软件搭建了具有垂直和水平关节的蛇形机器人模型,在蛇形曲线生成蜿蜒运动的基础上,采用逐节升降法实现了水中的上浮下潜运动步态.分析了蛇形机器人在水中运动过程中的位态、受力、关节力矩及运动效率的状况,为蛇形机器人水中运动的实用化提供数据参考,同时验证了逐节升降法实现蜿蜒下潜上浮的有效性.     

Identification of probabilistic approaches and map-based navigation in motion planning for mobile robots

Robot motion planning (RMP) develops a precise path between start and goal points for mobile robots in an unknown environment. RMP is a complex task when it needs to be planned for a group of robots in a coordinated environment with leader–follower relationship. The planned path might change depending upon the number of robots and the decision made. The decision made by each robot depends on the feedback received based on the subsequent action taken by other robots. In addition, the computational complexities depend upon factors such as communication between robots, the influence of moving obstacles and environment in which they are interacting. In order to explore further in the area of motion planning, it is felt that a comprehensive survey of available literature would support researchers working in RMP and hence the present paper. This paper reviews around 152 articles published in various international journals and conferences with more emphasis on articles published after 1960. In this work, recent activities carried out in the field of path planning for mobile robotics are critically evaluated and problems faced by the researchers are also highlighted. The focus is towards implementation of probabilistic algorithms, including Probabilistic Road Map and Simultaneous Localization and Mapping. Future research prospects in multi-robot path planning based on probabilistic approaches are also discussed.     

抛光工业机器人主动恒力装置设计研究

研究了工业机器人抛光中的恒力控制,针对传统的机器人恒力控制中既要对机器人进行力控制又要对机器人进行位置控制,导致工业机器人整体控制复杂,响应较慢,精度较低的问题,采用机器人力和位置分离的方式,设计了独立于机器人本体的主动恒力控制装置来解决机器人作业的力控制,使机器人力控制作业中不用考虑机器人的运动控制,从而达到解耦的效果。实验验证结果表明,设计的主动恒力装置提高了工业机器人力控制精度,具有良好的恒力控制性能。     

一种球形机器人高速直线运动的自适应控制方法

具备高速精准运动能力是球形机器人技术发展的重要方向。针对高速运动状态下外界扰动和系统抖振等因素对球形机器人精准直线运行产生的影响,开展面向高速直线运动的分数阶自适应分层积分滑模控制方法的研究。提出面向高速直线运动的球形机器人标准动力学模型并且以此作为控制方法的研究基础,将积分项和分数阶微积分项与分层滑模控制方法相结合,并且对高速运动过程中的未知扰动进行自适应评估和补偿,基于BYQ-GS高速运动球形机器人对该方法的控制效果展开验证。研究结果表明,在高速直线运动状态下,随着速度的增大,该控制方法能够有效提高系统响应速度、收敛速度、稳定性和鲁棒性,对球形机器人高速精准控制的实现有重要的意义。     

Smartdust 3D‐Printed Graphene‐Based Al/Ga Robots for Photocatalytic Degradation of Explosives

Milli/micro/nanorobots are considered smart devices able to convert energy taken from different sources into mechanical movement and accomplish the appointed tasks. Future advances and realization of these tiny devices are mostly limited by the narrow window of material choices, the fuel requirement, multistep surface functionalization, rational structural design, and propulsion ability in complex environments. All these aspects call for intensive improvements that may speed up the real application of such miniaturized robots. 3D‐printed graphene‐based smartdust robots provided with a magnetic response and filled with aluminum/gallium molten alloy (Al/Ga) for autonomous motion are presented. These robots can swim by reacting with the surrounding environment without adding any fuel. Because their outer surface is coated with a hydrogel/photocatalyst (chitosan/carbon nitride, C₃N₄) layer, these robots are used for the photocatalytic degradation of the picric acid as an explosive model molecule under visible light. The results show a fast and efficient degradation of picric acid that is attributed to a synergistic effect between the adsorption capability of the chitosan and the photocatalytic activity of C₃N₄ particles. This work provides added insight into the large‐scale fabrication, easy functionalization, and propulsion of tiny robots for environmental applications.     

基于行为的多移动机器人实时队形保持

多移动机器人队形问题是多机器人系统富有挑战性的研究方向之一。为了在动态、复杂的环境中实现队形的完全保持,设计了四种行为：奔向目标行为、保持队形行为、切线避碰行为和随机扰动行为,同时采用“leader更换”方法实现了机器人间的协调运动规划。仿真实验表明了所提行为策略可以有效的解决机器人运动过程中可能发生的冲突和死锁,确保了任务的顺利完成。     

A Light‐Powered Ultralight Tensegrity Robot with High Deformability and Load Capacity

Traditional hard robots often require complex motion‐control systems to accomplish various tasks, while applications of soft‐bodied robots are limited by their low load‐carrying capability. Herein, a hybrid tensegrity robot composed of both hard and soft materials is constructed, mimicking the musculoskeletal system of animals. Employing liquid crystal elastomer–carbon nanotube composites as artificial muscles in the tensegrity robot, it is demonstrated that the robot is extremely deformable, and its multidirectional locomotion can be entirely powered by light. The tensegrity robot is ultralight, highly scalable, has high load capacity, and can be precisely controlled to move along different paths on multiterrains. In addition, the robot also shows excellent resilience, deployability, and impact‐mitigation capability, making it an ideal platform for robotics for a wide range of applications.     

Elastic coupling of limb joints enables faster bipedal walking

The passive dynamics of bipedal limbs alone are sufficient to produce a walking motion, without need for control. Humans augment these dynamics with muscles, actively coordinated to produce stable and economical walking. Present robots using passive dynamics walk much slower, perhaps because they lack elastic muscles that couple the joints. Elastic properties are well known to enhance running gaits, but their effect on walking has yet to be explored. Here we use a computational model of dynamic walking to show that elastic joint coupling can help to coordinate faster walking. In walking powered by trailing leg push-off, the model''s speed is normally limited by a swing leg that moves too slowly to avoid stumbling. A uni-articular spring about the knee allows faster but uneconomical walking. A combination of uni-articular hip and knee springs can speed the legs for improved speed and economy, but not without the swing foot scuffing the ground. Bi-articular springs coupling the hips and knees can yield high economy and good ground clearance similar to humans. An important parameter is the knee-to-hip moment arm that greatly affects the existence and stability of gaits, and when selected appropriately can allow for a wide range of speeds. Elastic joint coupling may contribute to the economy and stability of human gait.     

Biomimetic six-axis robots replicate human cardiac papillary muscle motion: pioneering the next generation of biomechanical heart simulator technology

Papillary muscles serve as attachment points for chordae tendineae which anchor and position mitral valve leaflets for proper coaptation. As the ventricle contracts, the papillary muscles translate and rotate, impacting chordae and leaflet kinematics; this motion can be significantly affected in a diseased heart. In ex vivo heart simulation, an explanted valve is subjected to physiologic conditions and can be adapted to mimic a disease state, thus providing a valuable tool to quantitatively analyse biomechanics and optimize surgical valve repair. However, without the inclusion of papillary muscle motion, current simulators are limited in their ability to accurately replicate cardiac biomechanics. We developed and implemented image-guided papillary muscle (IPM) robots to mimic the precise motion of papillary muscles. The IPM robotic system was designed with six degrees of freedom to fully capture the native motion. Mathematical analysis was used to avoid singularity conditions, and a supercomputing cluster enabled the calculation of the system''s reachable workspace. The IPM robots were implemented in our heart simulator with motion prescribed by high-resolution human computed tomography images, revealing that papillary muscle motion significantly impacts the chordae force profile. Our IPM robotic system represents a significant advancement for ex vivo simulation, enabling more reliable cardiac simulations and repair optimizations.     

Soft Ultrathin Electronics Innervated Adaptive Fully Soft Robots

Soft robots outperform the conventional hard robots on significantly enhanced safety, adaptability, and complex motions. The development of fully soft robots, especially fully from smart soft materials to mimic soft animals, is still nascent. In addition, to date, existing soft robots cannot adapt themselves to the surrounding environment, i.e., sensing and adaptive motion or response, like animals. Here, compliant ultrathin sensing and actuating electronics innervated fully soft robots that can sense the environment and perform soft bodied crawling adaptively, mimicking an inchworm, are reported. The soft robots are constructed with actuators of open‐mesh shaped ultrathin deformable heaters, sensors of single‐crystal Si optoelectronic photodetectors, and thermally responsive artificial muscle of carbon‐black‐doped liquid‐crystal elastomer (LCE‐CB) nanocomposite. The results demonstrate that adaptive crawling locomotion can be realized through the conjugation of sensing and actuation, where the sensors sense the environment and actuators respond correspondingly to control the locomotion autonomously through regulating the deformation of LCE‐CB bimorphs and the locomotion of the robots. The strategy of innervating soft sensing and actuating electronics with artificial muscles paves the way for the development of smart autonomous soft robots.     

Technological unemployment,robotisation, and green deal: A story of unstable spillovers in China and South Korea (2008–2018)

The growing use of robots in the current ICT revolution has sparked a serious debate about the potential threat robots pose to human labour. In parallel, the convergence towards a more sustainable economy has caused a transformation of firms and a consequent restructuring of employment. In this article we investigate the problem of technological unemployment and environmental rebound effect by looking at how relationships between jobless growth, industrial robots usage, CO₂ emissions, and renewable energy consumption changed over time in China and South Korea. Findings from a competition model based on differential equations for the period 2008–2018 show that robots do not always increase unemployment growth. On the other hand, the type of relationship between unemployment and sustainable use of energy changes over time, questioning the possibility of a smart green new deal.     

Precision measurement and compensation of kinematic errors for industrial robots using artifact and machine learning

Industrial robots are widely used in various areas owing to their greater degrees of freedom (DOFs) and larger operation space compared with traditional frame movement systems involving sliding and rotational stages. However, the geometrical transfer of joint kinematic errors and the relatively weak rigidity of industrial robots compared with frame movement systems decrease their absolute kinematic accuracy, thereby limiting their further application in ultraprecision manufacturing. This imposes a stringent requirement for improving the absolute kinematic accuracy of industrial robots in terms of the position and orientation of the robot arm end. Current measurement and compensation methods for industrial robots either require expensive measuring systems, producing positioning or orientation errors, or offer low measurement accuracy. Herein, a kinematic calibration method for an industrial robot using an artifact with a hybrid spherical and ellipsoid surface is proposed. A system with submicrometric precision for measuring the position and orientation of the robot arm end is developed using laser displacement sensors. Subsequently, a novel kinematic error compensating method involving both a residual learning algorithm and a neural network is proposed to compensate for nonlinear errors. A six-layer recurrent neural network (RNN) is designed to compensate for the kinematic nonlinear errors of a six-DOF industrial robot. The results validate the feasibility of the proposed method for measuring the kinematic errors of industrial robots, and the compensation method based on the RNN improves the accuracy via parameter fitting. Experimental studies show that the measuring system and compensation method can reduce motion errors by more than 30%. The present study provides a feasible and economic approach for measuring and improving the motion accuracy of an industrial robot at the submicrometric measurement level.The full text can be downloaded at https://link.springer.com/article/10.1007/s40436-022-00400-6     

移动机器人运动规划研究综述

机器人运动规划是移动机器人导航的核心技术之一。40多年来，运动规划技术发展迅速，涌现出了许多规划算法，但因为环境描述方式差异巨大，技术差别大，实验比较难度较大。在总结机器人发展史上具有典型意义的规划算法的基础上，提出了路径规划算法的评价标准和形式化描述方式，介绍了每种算法的原理或技术，从搜索策略和环境建模的角度将它们分为四大类，分别是基于自由空间几何构造的规划算法、前向图搜索算法、基于随机采样的运动规划算法以及智能化规划算法，并按照提出的标准比较它们的性能。