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Research on dynamic parameter identification and collision detection method for cooperative robots 协作机器人动态参数识别与碰撞检测方法研究
IF 1.8 4区 计算机科学 Q3 ENGINEERING, INDUSTRIAL Pub Date : 2023-09-12 DOI: 10.1108/ir-05-2023-0091
Shuwen Sun, Chenyu Song, Bo Wang, Haiming Huang
PurposeThe safety performance of cooperative robots is particularly important. This paper aims to study collision detection and response of cooperative robots, which meet the lightweight requirements of cooperative robots and help to ensure the safety of humans and robots.Design/methodology/approachThis paper proposes a collision detection, recognition and response method based on dynamic models. First, this paper identifies the dynamic model of the robot. Second, an external torque observer is established based on the model, and a dynamic threshold collision detection method is designed to reduce the interference of model uncertainty on collision detection. Finally, a collision position and direction estimation method is designed, and a robot collision response strategy is proposed to reduce the harm caused by collisions to humans.FindingsComparative experiments are conducted on static threshold and dynamic threshold collision detection, and the results showed that the static threshold only detected one collision while the dynamic threshold could detect all collisions. Conducting collision position and direction estimation and collision response experiments, and the results show that this method can determine the location and direction of collision occurrence, and enable the robot to achieve collision separation.Originality/valueThis paper designs a dynamic threshold collision detection method that does not require external sensors. Compared with static threshold collision detection methods, this method can significantly improve the sensitivity of collision detection. This paper also proposes a collision position direction estimation method and collision separation response strategy, which can enable robots to achieve post collision separation and improve the safety of cooperative robots.
目的协作机器人的安全性能尤为重要。本文旨在研究协作机器人的碰撞检测和响应,以满足协作机器人的轻量化要求,并有助于确保人与机器人的安全。本文提出了一种基于动态模型的碰撞检测、识别和响应方法。首先,本文对机器人的动力学模型进行了辨识。其次,基于模型建立外部力矩观测器,设计动态阈值碰撞检测方法,降低模型不确定性对碰撞检测的干扰;最后,设计了碰撞位置和方向估计方法,并提出了机器人碰撞响应策略,以减少碰撞对人体的伤害。对静态阈值和动态阈值碰撞检测进行了对比实验,结果表明,静态阈值只能检测到一次碰撞,而动态阈值可以检测到所有碰撞。进行碰撞位置和方向估计及碰撞响应实验,结果表明,该方法可以确定碰撞发生的位置和方向,并使机器人实现碰撞分离。本文设计了一种不需要外部传感器的动态阈值碰撞检测方法。与静态阈值碰撞检测方法相比,该方法可以显著提高碰撞检测的灵敏度。本文还提出了一种碰撞位置方向估计方法和碰撞分离响应策略,使机器人能够实现碰撞后分离,提高协作机器人的安全性。
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引用次数: 0
Sequential calibration of transmission ratios for joints of 6-DOF serial industrial robots based on laser tracker 基于激光跟踪仪的六自由度串联工业机器人关节传动比顺序标定
IF 1.8 4区 计算机科学 Q3 ENGINEERING, INDUSTRIAL Pub Date : 2023-09-12 DOI: 10.1108/ir-05-2023-0115
Ling Wang, Xiaoliang Wu, Zeng Kang, Yanfeng Gao, Xiai Chen, Binrui Wang
PurposeIn traditional calibration methods of kinematics parameters of industrial robots, dozens of model parameters are identified together based on an optimization procedure. Due to different contributions of model parameter errors to the tool center point positioning error of industrial robots, obtaining good results for all model parameters is very difficult. Therefore, the purpose of this paper is to propose a sequential calibration method specifically for transmission ratio parameters, which includes reduction ratios and coupling ratios of industrial robot joints.Design/methodology/approachThe ABB IRB 1410 industrial robot is considered as an example in this study. The transmission ratios for each joint of the robot are identified using the spatial circle fitting method based on spatial vectors, which fit the center and radius of joint rotation with the least squares optimization algorithm. In addition, a method based on the Rodrigues’ formula is designed and presented for identifying the actual coupling ratio of the robot. Subsequently, an experiment is carried out to verify the proposed sequential calibration method of transmission ratios.FindingsIn this experiment, the actual positions of the linkages before and after joint rotations are measured by a laser tracker. Accurate results of the reduction ratios and the coupling ratios are calculated, and the results are verified experimentally. The results show that by calibrating the reduction ratios and coupling ratios of the ABB robot, the rotation angle errors of the robot joints can be reduced.Originality/valueThe authors propose a sequential calibration method for transmission ratio parameters, including reduction ratios and coupling ratios of industrial robot joints. An experiment is carried out to verify this proposed sequential calibration method. This study may be beneficial for calibrating the kinematic parameters of industrial robots and improving their positioning accuracy.
目的在传统的工业机器人运动学参数标定方法中,基于优化过程对数十个模型参数进行综合辨识。由于模型参数误差对工业机器人刀具中心点定位误差的贡献不同,对所有模型参数都要得到较好的结果是非常困难的。因此,本文的目的是提出一种针对传动比参数的顺序校准方法,其中包括工业机器人关节的减速比和耦合比。设计/方法/方法本研究以ABB IRB 1410工业机器人为例。采用基于空间矢量的空间圆拟合方法确定机器人各关节的传动比,并用最小二乘优化算法拟合关节旋转的中心和半径。此外,设计并提出了一种基于Rodrigues公式的机器人实际耦合比辨识方法。随后,通过实验验证了所提出的传动比顺序标定方法。在本实验中,用激光跟踪仪测量了关节旋转前后连杆的实际位置。计算了减速比和耦合比的精确结果,并进行了实验验证。结果表明,通过标定ABB机器人的减速比和耦合比,可以减小机器人关节的转角误差。提出了一种工业机器人关节传动比参数的顺序标定方法,包括减速比和耦合比。通过实验验证了该方法的正确性。该研究对工业机器人运动学参数的标定和定位精度的提高具有一定的指导意义。
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引用次数: 0
Design and analysis of a continuum manipulator for use in narrow spaces 窄空间连续机械臂的设计与分析
IF 1.8 4区 计算机科学 Q3 ENGINEERING, INDUSTRIAL Pub Date : 2023-09-08 DOI: 10.1108/ir-02-2023-0027
Fei Qi, Dongming Bai, Xiaoming Dou, Heng Zhang, Haishan Pei, Jing-de Zhu
PurposeThis paper aims to present a kinematics analysis method and statics based control of the continuum robot with mortise and tenon joints to achieve better control performance of the robot.Design/methodology/approachThe kinematics model is derived by the geometric analysis method under the piecewise constant curvature assumption, and the workspace and dexterity of the proposed robot are analyzed to optimize its structure parameters. Moreover, the statics model is established by the principle of virtual work, which is used to analyze the mapping relationship between the bending deformation and the applied forces/torques. To improve the control accuracy of the robot, a model-based controller is put forward.FindingsResults of the experiments verify the feasibility of the proposed continuum structure and the correctness of the established model and the control method. The force deviation between the theoretical value and the actual value is relatively small, and the mean value of the deviation between the driving forces is only 0.46 N, which verify the established statics model and the controller.Originality/valueThe proposed model and motion controller can realize its accurate bending control with a few deviations, which can be used as the reference for the motion planning and dynamic model of the continuum robot.
目的提出一种基于运动学分析和静力学控制的榫卯连续体机器人控制方法,以提高机器人的控制性能。在分段常曲率假设下,采用几何分析法推导了机器人的运动学模型,分析了机器人的工作空间和灵巧性,优化了机器人的结构参数。利用虚功原理建立了弯曲静力学模型,分析了弯曲变形与施加的力/力矩之间的映射关系。为了提高机器人的控制精度,提出了一种基于模型的控制器。实验结果验证了所提出的连续体结构的可行性以及所建立的模型和控制方法的正确性。理论值与实测值之间的力偏差较小,驱动力之间的偏差均值仅为0.46 N,验证了所建立的静力学模型和控制器的正确性。所提出的模型和运动控制器可以实现其精确的弯曲控制,误差较小,可为连续体机器人的运动规划和动力学建模提供参考。
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引用次数: 0
Tightly coupled IMU-Laser-RTK odometry algorithm for underground multi-layer and large-scale environment 地下多层大尺度环境下紧密耦合IMU-Laser-RTK测程算法
IF 1.8 4区 计算机科学 Q3 ENGINEERING, INDUSTRIAL Pub Date : 2023-09-07 DOI: 10.1108/ir-11-2022-0281
Minghao Wang, Ming Cong, Dong Liu, Yuqing Du, Xiaojing Tian, Bing Li
PurposeThe purpose of this study is to designed a robot odometry based on three dimensional (3D) laser point cloud data, inertial measurement unit (IMU) data and real-time kinematic (RTK) data in underground spatial features and gravity fluctuations environment. This method improves the mapping accuracy in two types of underground space: multi-layer space and large-scale scenarios.Design/methodology/approachAn IMU–Laser–RTK fusion mapping algorithm based on Iterative Kalman Filter was proposed, and the observation equation and Jacobian matrix were derived. Aiming at the problem of inaccurate gravity estimation, the optimization of gravity is transformed into the optimization of SO(3), which avoids the problem of gravity over-parameterization.FindingsCompared with the optimization method, the computational cost is reduced. Without relying on the wheel speed odometer, the robot synchronization localization and 3D environment modeling for multi-layer space are realized. The performance of the proposed algorithm is tested and compared in two types of underground space, and the robustness and accuracy in multi-layer space and large-scale scenarios are verified. The results show that the root mean square error of the proposed algorithm is 0.061 m, which achieves higher accuracy than other algorithms.Originality/valueBased on the problem of large loop and low feature scale, this algorithm can better complete the map loop and self-positioning, and its root mean square error is more than double compared with other methods. The method proposed in this paper can better complete the autonomous positioning of the robot in the underground space with hierarchical feature degradation, and at the same time, an accurate 3D map can be constructed for subsequent research.
目的设计基于三维激光点云数据、惯性测量单元(IMU)数据和实时运动学(RTK)数据的地下空间特征和重力波动环境下的机器人里程计。该方法提高了地下空间在多层空间和大尺度场景下的成图精度。提出了一种基于迭代卡尔曼滤波的IMU-Laser-RTK融合映射算法,推导了观测方程和雅可比矩阵。针对重力估计不准确的问题,将重力优化转化为SO(3)的优化,避免了重力过参数化问题。结果:与优化方法相比,计算量减少。在不依赖轮速里程计的情况下,实现了机器人的同步定位和多层空间的三维环境建模。在两类地下空间中进行了性能测试和比较,验证了算法在多层空间和大尺度场景下的鲁棒性和准确性。结果表明,该算法的均方根误差为0.061 m,比其他算法具有更高的精度。独创性/价值基于大回路、低特征尺度的问题,该算法能较好地完成地图回路和自定位,其均方根误差比其他方法大一倍以上。本文提出的方法可以更好地完成机器人在具有层次特征退化的地下空间中的自主定位,同时可以为后续研究构建精确的三维地图。
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引用次数: 0
Design, modeling and kinematic analysis of a multi-configuration dexterous hand with integrated high-dimensional sensors 集成高维传感器的多构型灵巧手的设计、建模及运动学分析
IF 1.8 4区 计算机科学 Q3 ENGINEERING, INDUSTRIAL Pub Date : 2023-08-22 DOI: 10.1108/ir-07-2023-0161
Shuang Feng, Yang Du, Shaodong Li, Mingqi Chen
PurposeThis study aims to introduce a multi-configuration, three-finger dexterous hand with integrated high-dimensional sensors and provides an analysis of its design, modeling and kinematics.Design/methodology/approachA mechanical design scheme of the three-finger dexterous hand with a reconfigurable palm is proposed based on the existing research on dexterous hands. The reconfigurable palm design enables the dexterous hand to achieve four grasping modes to adapt to multiple grasping tasks. To further enhance perception, two six-axis force and torque sensors are integrated into each finger. The forward and inverse kinematics equations of the dexterous hand are derived using the D-H method for kinematics modeling, thus providing a theoretical model for index analysis. The performance is evaluated using three widely applied indicators: workspace, interactivity of fingers and manipulability.FindingsThe results of kinematics analysis show that the proposed hand has excellent dexterity. Additionally, three different experiments are conducted based on the proposed hand. The performance of the dexterous hand is also verified by fingertip force, motion accuracy test, grasping and in-hand manipulation experiments based on Feix taxonomy. The results show that the dexterous hand has good grasping ability, reproducing 82% of the natural movement of the human hand in daily grasping activities and achieving in-hand manipulations such as translation and rotation.Originality/valueA novel three-finger dexterous hand with multi-configuration and integrated high-dimensional sensors is proposed. It performs better than the previously designed dexterous hand in actual experiments and kinematic performance analysis.
目的介绍一种集成了高维传感器的多构型三指灵巧手,并对其设计、建模和运动学进行了分析。在现有灵巧手研究的基础上,提出了手掌可重构的三指灵巧手的机械设计方案。可重构手掌设计使灵巧的手能够实现四种抓取模式,以适应多种抓取任务。为了进一步增强感知,每个手指都集成了两个六轴力和扭矩传感器。采用D-H法进行运动学建模,推导了灵巧手的正运动学和逆运动学方程,为指标分析提供了理论模型。使用三个广泛应用的指标来评估性能:工作空间,手指的交互性和可操作性。运动学分析结果表明,所设计的机械手具有良好的灵巧性。此外,基于所提出的手进行了三个不同的实验。通过指尖力、运动精度测试、抓握和基于Feix分类法的手部操作实验验证了灵巧手的性能。结果表明,灵巧手具有良好的抓取能力,可以再现82%的日常抓取活动中人手的自然动作,实现平移、旋转等手部操作。提出了一种新型的多构型、集成高维传感器的三指灵巧手。在实际实验和运动性能分析中,该方法优于先前设计的灵巧手。
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引用次数: 0
Bin picking: a review of recent developments 拾荒:回顾最近的发展
IF 1.8 4区 计算机科学 Q3 ENGINEERING, INDUSTRIAL Pub Date : 2023-08-15 DOI: 10.1108/ir-07-2023-0167
R. Bogue
PurposeThe purpose of this paper is to provide an insight into the present-day state of bin picking by considering research, technology, products and applications.Design/methodology/approachFollowing a short introduction, this first provides examples of recent bin picking research. It then discusses a selection of commercial product developments and applications. Finally, brief conclusions are drawn.FindingsBin picking has the potential to eliminate repetitive, manual part handling practices in many sectors of the manufacturing and logistics industries. Systems combine robotic gripping and manipulation with machine vision and specialist software and tend to be complex to install and commission. They are produced by robot manufacturers, system integrators, software developers and machine vision specialists and all are constantly developing and improving the technology. These developments are supported by a strong academic research effort, much involving artificial intelligence methods, and while the technology is evolving rapidly, it is yet to reach the point where deployments are routine and widespread.Originality/valueThis provides a timely review of recent bin picking research and commercial developments.
本文的目的是通过研究、技术、产品和应用来深入了解当前的垃圾箱拾取状况。设计/方法/方法在一个简短的介绍之后,这首先提供了最近的垃圾箱拾取研究的例子。然后讨论了商业产品开发和应用的选择。最后,得出了简要的结论。调查结果在制造和物流行业的许多部门中,bin拣选有可能消除重复的、人工的零件处理实践。该系统将机器人抓取和操作与机器视觉和专业软件相结合,安装和调试往往很复杂。它们由机器人制造商、系统集成商、软件开发商和机器视觉专家生产,所有人都在不断开发和改进这项技术。这些发展得到了强大的学术研究努力的支持,其中大部分涉及人工智能方法,尽管该技术正在迅速发展,但尚未达到常规部署和广泛部署的程度。原创性/价值这提供了一个及时的回顾,最近的垃圾桶拣拣研究和商业发展。
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引用次数: 0
Manipulability optimization of redundant manipulators using reinforcement learning 基于强化学习的冗余机械手可操纵性优化
IF 1.8 4区 计算机科学 Q3 ENGINEERING, INDUSTRIAL Pub Date : 2023-07-05 DOI: 10.1108/ir-01-2023-0002
Haoqiang Yang, Xinliang Li, Deshan Meng, Xueqian Wang, Bin Liang
PurposeThe purpose of this paper is using a model-free reinforcement learning (RL) algorithm to optimize manipulability which can overcome difficulties of dilemmas of matrix inversion, complicated formula transformation and expensive calculation time.Design/methodology/approachManipulability optimization is an effective way to solve the singularity problem arising in manipulator control. Some control schemes are proposed to optimize the manipulability during trajectory tracking, but they involve the dilemmas of matrix inversion, complicated formula transformation and expensive calculation time.FindingsThe redundant manipulator trained by RL can adjust its configuration in real-time to optimize the manipulability in an inverse-free manner while tracking the desired trajectory. Computer simulations and physics experiments demonstrate that compared with the existing methods, the average manipulability is increased by 58.9%, and the calculation time is reduced to 17.9%. Therefore, the proposed method effectively optimizes the manipulability, and the calculation time is significantly shortened.Originality/valueTo the best of the authors’ knowledge, this is the first method to optimize manipulability using RL during trajectory tracking. The authors compare their approach to existing singularity avoidance and manipulability maximization techniques, and prove that their method has better optimization effects and less computing time.
目的利用无模型强化学习(RL)算法优化可操作性,克服了矩阵反演、公式变换复杂、计算时间昂贵等难题。可操纵性优化是解决机械手控制中奇异性问题的有效途径。为了优化轨迹跟踪过程中的可操纵性,提出了一些控制方案,但存在矩阵反演、公式变换复杂、计算时间昂贵等问题。结果:通过RL训练的冗余机械手能够实时调整构型,在跟踪期望轨迹的同时实现无逆操纵性优化。计算机仿真和物理实验表明,与现有方法相比,该方法的平均可操纵性提高了58.9%,计算时间缩短到17.9%。因此,该方法有效地优化了可操纵性,大大缩短了计算时间。原创性/价值据作者所知,这是在轨迹跟踪过程中使用强化学习优化可操控性的第一种方法。将该方法与现有的奇点避免和可操纵性最大化方法进行了比较,证明了该方法具有更好的优化效果和更少的计算时间。
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引用次数: 0
Shape perception of soft hand based on dual-signal comparison contact detection 基于双信号比较接触检测的软手形状感知
IF 1.8 4区 计算机科学 Q3 ENGINEERING, INDUSTRIAL Pub Date : 2023-07-04 DOI: 10.1108/ir-02-2023-0033
Kai Shi, Jun Yu Li, Gang Bao
PurposeThe structural adaptive ability of the soft robot is fully demonstrated in the grasping task of the soft hand. A soft hand can easily realize the envelope operation of the object without planning. With the continuous development of robot applications, researchers are no longer satisfied with the ability of the soft hand to grasp. The purpose of this paper is to perceive the object’s shape while grasping to provide a decision-making basis for more intelligent robot applications.Design/methodology/approachThis paper proposes a dual-signal comparison method to obtain the fingertip position. The dual signal includes the displacement calculated by the static model without considering the external load change and the displacement calculated by the bending sensor. The dual-signal comparison method can use the obvious change trend difference between the above two signals in the hover and contact states to identify the touch position. The authors make the soft hand scan around the object through touch operation to detect the object’s shape, and the tracks of every touch fingertip position can envelop the object’s shape.FindingsThe experimental results show that the dual-signal comparison method can accurately identify the contact moment of soft fingers. This detection method makes the soft hand develop the shape detection ability. The soft hand in the experiment can perceive squares, circles and a few other complex shapes.Originality/valueThe dual-signal comparison method proposed in this paper can detect a touch action by using the signal change trend when the working condition suddenly changes with the rough robotic model and sensing, thus improving the utilization value of the measured signal. The problems of large model errors and inaccurate sensors also negatively impact the use of other soft robots. It is generally difficult to achieve good results by directly using these models and sensors with the thinking of rigid robot analysis. The dual-signal comparison method in this paper can provide some reference for this aspect.
目的在软手抓取任务中充分展示了柔性机器人的结构自适应能力。一只柔软的手可以很容易地实现物体的包络操作,而不需要规划。随着机器人应用的不断发展,研究人员已经不再满足于软手的抓取能力。本文的目的是在抓取的同时感知物体的形状,为更智能的机器人应用提供决策依据。设计/方法/方法本文提出了一种双信号比较方法来获得指尖位置。双信号包括不考虑外载荷变化的静态模型计算的位移和弯曲传感器计算的位移。双信号比较法可以利用上述两种信号在悬停状态和接触状态下的明显变化趋势差来识别触摸位置。作者通过触摸操作使软手在物体周围扫描以检测物体的形状,并且每个触摸指尖位置的轨迹可以包裹物体的形状。实验结果表明,双信号比较方法可以准确识别柔软手指的接触力矩。这种检测方法使柔软的手具有形状检测能力。实验中的软手可以感知正方形、圆形和其他一些复杂的形状。本文提出的双信号比较法可以利用粗糙机器人模型和传感在工作状态突然变化时的信号变化趋势来检测触摸动作,从而提高了测量信号的利用价值。大模型误差和不准确传感器的问题也对其他软机器人的使用产生了负面影响。以刚性机器人分析的思维,直接使用这些模型和传感器,一般难以取得良好的效果。本文的双信号比较方法可以为这方面提供一些参考。
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引用次数: 0
Design and performance of a slender soft continuum manipulator for tall structure inspection 一种细长柔性连续体高结构检测机械手的设计与性能
IF 1.8 4区 计算机科学 Q3 ENGINEERING, INDUSTRIAL Pub Date : 2023-06-16 DOI: 10.1108/ir-03-2023-0057
Mohamed Tahir Shoani, Mohamed Najib Ribuan, Ahmad Athif Mohd Faudzi
PurposeThe current methods for inspecting tall or deep structures such as towers, chimneys, silos, and wells suffer from certain constraints. Manual and assisted inspection methods including humans, drones, wall climbing robots, and others are either costly, have a limited operation time, or affected by field conditions, such as temperature and radiation. This study aims to overcome the presented challenges through a teleoperated soft continuum manipulator capable of inspecting tall or deep structures with high resolution, an unlimited operation time and the ability to use different arms of the manipulator for different environments and structure sizes.Design/methodology/approachThe teleoperated manipulator uses one rotary and two tendon actuators to reach and inspect the interior of a tall (or deep) structure. A sliding part along the manipulator’s body (arm constrainer and tendon router) induces a variable-length bending segment, allowing an inspection camera to be placed at different distances from the desired location.FindingsThe experiments confirmed the manipulator’s ability to inspect different locations in the structure’s interior. The manipulator also demonstrated a submillimeter motion resolution vertically and a 2.5 mm per step horizontally. The inspection time of the full structure was 48.53 min in the step-by-step mode and was calculated to be 4.23 min in the continuous mode.Originality/valueThe presented manipulator offers several design novelties: the arm’s thin-wide cross-section, the variable-length bending segment in a fixed-length body, the external rolling tendon routing and the ability to easily replace the arm with another of different material or dimensions to suite different structures and environments.
目的目前用于检查高层或深层结构(如塔、烟囱、筒仓和井)的方法受到一定的限制。人工和辅助检测方法,包括人工、无人机、爬壁机器人等,要么成本高昂,要么操作时间有限,要么受现场条件(如温度和辐射)的影响。本研究旨在通过一种远程操作的软连续机械臂来克服目前的挑战,该机械臂能够以高分辨率、无限的操作时间和针对不同环境和结构尺寸使用不同机械臂的能力来检测高层或深层结构。设计/方法/方法遥控机械手使用一个旋转驱动器和两个肌腱驱动器来到达并检查高(或深)结构的内部。沿着机械手身体(手臂约束器和肌腱路由器)的滑动部分诱导可变长度的弯曲段,允许检查摄像机放置在距离所需位置的不同距离上。实验证实了机械手检查结构内部不同位置的能力。该机械手还展示了亚毫米的垂直运动分辨率和2.5毫米的水平运动分辨率。在分步模式下,整个结构的检测时间为48.53 min,在连续模式下计算为4.23 min。所展示的机械手提供了几个设计上的新颖之处:臂的横截面薄而宽,在固定长度的主体中有可变长度的弯曲段,外部滚动肌腱路由,以及可以轻松地用不同材料或尺寸的另一个臂来替换臂,以适应不同的结构和环境。
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引用次数: 0
A nonlinear robot joint friction compensation method including stick and sliding characteristics 一种包含粘滞和滑动特性的非线性机器人关节摩擦补偿方法
IF 1.8 4区 计算机科学 Q3 ENGINEERING, INDUSTRIAL Pub Date : 2023-06-06 DOI: 10.1108/ir-12-2022-0322
Yanli Feng, Kecheng Zhang, Haoyu Li, Jingyu Wang
PurposeDue to dynamic model is the basis of realizing various robot control functions, and it determines the robot control performance to a large extent, this paper aims to improve the accuracy of dynamic model for n-Degree of Freedom (DOF) serial robot.Design/methodology/approachThis paper exploits a combination of the link dynamical system and the friction model to create robot dynamic behaviors. A practical approach to identify the nonlinear joint friction parameters including the slip properties in sliding phase and the stick characteristics in presliding phase is presented. Afterward, an adaptive variable-step moving average method is proposed to effectively reduce the noise impact on the collected data. Furthermore, a radial basis function neural network-based friction estimator for varying loads is trained to compensate the nonlinear effects of load on friction during robot joint moving.FindingsExperiment validations are carried out on all the joints of a 6-DOF industrial robot. The experimental results of joint torque estimation demonstrate that the proposed strategy significantly improves the accuracy of the robot dynamic model, and the prediction effect of the proposed method is better than that of existing methods.Originality/valueThe proposed method extends the robot dynamic model with friction compensation, which includes the nonlinear effects of joint stick motion, joint sliding motion and load attached to the end-effector.
由于动态模型是实现机器人各种控制功能的基础,在很大程度上决定着机器人的控制性能,因此本文旨在提高n自由度(DOF)串联机器人动态模型的精度。设计/方法/方法本文将连杆动力系统与摩擦模型相结合来创建机器人的动力学行为。提出了一种实用的方法来识别关节的非线性摩擦参数,包括滑动阶段的滑移特性和预滑动阶段的粘滞特性。然后,提出了一种自适应变步长移动平均方法,有效地降低了噪声对采集数据的影响。此外,训练了一种基于径向基函数神经网络的变载荷摩擦估计器,以补偿机器人关节运动过程中载荷对摩擦的非线性影响。对六自由度工业机器人的所有关节进行了实验验证。关节力矩估计的实验结果表明,该策略显著提高了机器人动力学模型的精度,预测效果优于现有方法。该方法对机器人动力学模型进行了扩展,并引入了摩擦补偿,该模型包含了关节粘连运动、关节滑动运动和末端执行器负载的非线性效应。
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引用次数: 0
期刊
Industrial Robot-The International Journal of Robotics Research and Application
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