Robust object manipulation for tactile-based blind grasping

Tactile-based blind grasping addresses realistic robotic grasping in which the hand only has access to proprioceptive and tactile sensors. The robotic hand has no prior knowledge of the object/grasp properties, such as object weight, inertia, and shape. There exists no manipulation controller that rigorously guarantees object manipulation in such a setting. Here, a robust control law is proposed for object manipulation in tactile-based blind grasping. The analysis ensures semi-global asymptotic and exponential stability in the presence of model uncertainties and external disturbances that are neglected in related work. Simulation and hardware results validate the effectiveness of the proposed approach.     

Dynamic Analysis and Control Synthesis of Undesired Slippage of End-Effectors in a Cooperative Grasping

This paper addresses dynamic analysis and control synthesis of object grasping in a cooperative multirobot system with n-serial manipulators from an undesired slippage point of view. Two control approaches are presented in this article; a modified version of a conventional method in grasp synthesis and a new method based on a new modeling of system dynamics. A new formulation for frictional contact is used in dynamical modeling, where equality and inequality equations of the standard Coulomb friction model are all converted to a single second-order differential equation. A multiphase controller is utilized to control the object trajectory tracking as well as object slippage in the new control approach. Performance and robustness of both approaches are studied numerically. The results show superiority of the new method and its desirable and excellent performance.     

Two-arm manipulation tasks with friction-assisted grasping

—The main objective of this paper is to study human dual-arm manipulation tasks and to develop a computational model that predicts the trajectories and force distribution for the coordination of two arms moving an object between two given positions and orientations in a horizontal plane. Our ultimate goal is to understand the dynamics of human dual-arm coordination in order to develop better robot control algorithms. We propose a computational model based on the hypothesis proposed by Uno et al. that suggests that human movements minimize the integral of the norm of the rate of change of actuator torques. We compare the experimental trajectories and force distributions with those obtained from the computational model. The observed trajectories show a significant degree of repeatability across trials and across subjects. We show that the computational model predicts the trajectories and the distribution of forces (torques) for a certain class of trajectories. However, the trajectories in the sagittal and frontal plane are characterized by asymmetric features that are hard to model using any integral cost function. Finally, we show that the computational model can be used to generate smooth trajectories and actuator forces for cooperating robots and discuss the advantages of such an approach to motion planning.     

A differential-geometric approach for 2D and 3D object grasping and manipulation

This article presents an expository work on a differential-geometric treatment of fundamental problems of 2D and 3D object grasping and manipulation by a pair of robot fingers with multi-joints under holonomic or nonholonomic constraints. First, Lagrange’s equation of motion of a fingers-object system whose motion is confined to a vertical plane is derived under holonomic constraints when rolling contacts between finger-ends and object surfaces are permitted. Then, a class of control signals called “blind grasping” and constructed without knowing the object kinematics or using any external sensing like vision or tactile sensation is shown to realize stable object grasping in a dynamic sense. Stability of motion and its convergence to an equibrium manifold are treated on the basis of differential geometry of solution trajectories of the closed-loop dynamics on the constraint manifolds. Second, a mathematical model of 3D object grasping and manipulation by a pair of multi-joint robot fingers is derived under the assumption that spinning motion of rotation around the opposing axis between contact points does no more arise. It is shown that, differently from the 2D case, the instantaneous axis of rotation of the object is time-varying, which induces a nonholonomic constraint expressed as a linear differential equation of rotational motion of the pinched object. It is shown that there is a class of control signals constructed without knowing the object kinematics or using external sensings that can realize “blind grasping” in a dynamic sense. Finally, it is shown that the proposed differential geometric treatment of stability can naturally cope with redundancy resolution problems of surplus degrees-of-freedom (d.f.) of the overall fingers-object system, which is closely related to Bernstein’s d.f. problem.     

A brief review of affordance in robotic manipulation research

Abstract

This paper presents a brief review of affordance research in robotics, with special concentrations on its applications in grasping and manipulation of objects. The concept of affordance could be a key to realize human-like advanced manipulation intelligence. First, we discuss the concept of affordance while associating with the applications in robotics. Then, we intensively explore the studies that utilize affordance for robotic manipulation applications, such as object recognition, grasping, and object manipulation including tool-use. They obtain and use affordance by several ways like learning from human, using simulation, and real-world execution. Moreover, we show our current work, which is a cloud database for advanced manipulation intelligence. The database accumulates various data related to manipulation task execution and will be an open platform to leverage various affordance techniques.     

A mobile dual-arm manipulation robot system for stocking and disposing of items in a convenience store by using universal vacuum grippers for grasping items

ABSTRACT

A mobile dual-arm robot with universal vacuum grippers (UVG) for performing stocking and disposing tasks was developed. The robot grasps items in the tasks by using UVGs whose surface adapts to the various shapes of the items. A selection algorithm that determines whether the robot should use one or both manipulators to arrange an item was also developed. A ‘reachable-grasp pose’ is defined as a pose in which the robot’s UVG can easily place an item with a target attitude if it grasps the item. By using the selection algorithm, the robot re-grasps the item by adopting the reachable-grasp pose if the two manipulators do not collide when one is in the current grasp pose and the other is in the reachable-grasp pose. The robot system won the third prize of the Future Convenience Store Challenge 2018. In experiments on stocking and disposing tasks, the robot system achieved success rates of 100% for the stocking task and 80% for the disposing task. We believe that the results of this study will help researchers to develop a robot system for not only the stocking and disposing tasks but also other tasks in convenience stores (like customer interaction).     

野外移动机器人滑动效应的在线建模和跟踪控制

针对野外移动机器人的滑动效益建模和补偿控制问题进行了研究.以履带式移动机器人为研究对象,将履带和地面之间的滑动效应建模为时变的滑动参数,由此建立起带滑动参数的机器人运动学和动力学模型,并采用基于方根无色卡尔曼滤波(SR-uKF)的在线非线性估计方法对机器人的位姿和滑动参数进行联合估计.在此基础上,提出了一种基于动态反馈...     

RUR53: an unmanned ground vehicle for navigation,recognition, and manipulation

ABSTRACT

This paper proposes RUR53: an Unmanned Ground Vehicle able to navigate through, identify, and reach areas of interest. There, it can recognize, localize, and manipulate work tools to perform both indoor and outdoor complex tasks. Indeed, a wide range of sensors composes the robot and enables it to perceive vast workspaces, reach distant targets, and face the uncertainties of the real world. Precise object detection is also guaranteed, essential to manipulate objects of different shapes and materials. Moreover, a customized 3-finger gripper makes the gripping mode suitable for any lightweight object. Two modalities are proposed: autonomous and teleoperated, letting both unskilled and skilled human operators easily adapt the system to complete personalized tasks. The paper exhaustively describes RUR53 architecture and demonstrates its good performance while executing both indoor and outdoor navigation and manipulation tasks. A specific case study is described where the proposed modular architecture allows to easily switch to a semi-teleoperated mode: the 2017 Mohamed Bin Zayed International Robotics Challenge, where our team ranked third in the Grand Challenge in collaboration with the Czech Technical University in Prague, the University of Pennsylvania, and the University of Lincoln (UK).     

基于运动控制针刺手法仪的工程研究

通过针刺手法的工程理论分析,提出了基于运动控制的针刺手法的实现原理和方法,在此基础上研制开发了针刺手法仪,为抢救针灸名家手法提供了一个有效途径,对针灸工程化进行了全新的探索。     

Analysis of the musculoskeletal system of the hand and forearm during a cylinder grasping task

Musculoskeletal disorders of the hand are mostly due to repeated or awkward manual tasks in the work environment and are considered a public health issue. To prevent their development, it is necessary to understand and investigate the biomechanical behavior of the musculoskeletal system during the movement. In this study a biomechanical analysis of the upper extremity during a cylinder grasping task is conducted by using a parameterized musculoskeletal model of the hand and forearm. The proposed model is composed of 21 segments, 28 musculotendon units, and 20 joints providing 24 degrees of freedom. Boundary conditions of the model are defined by the three-dimensional coordinates of 43 external markers fixed to bony landmarks of the hand and forearm and tracked with an optoelectronic motion capture system. External marker positions from five healthy participants were used to test the model. A task consisting of closing and opening fingers around a cylinder 25 mm in diameter was investigated. Based on experimental kinematic data, an inverse dynamics process was performed to calculate output data of the model (joint angles, musculotendon unit shortening and lengthening patterns). Finally, based on an optimization procedure, joint loads and musculotendon forces were computed in a forward dynamics simulation. Results of this study assessed reproducibility and consistency of the biomechanical behavior of the musculoskeletal hand system.     

Viscoelastic model based force control for soft tissue interaction and its application in physiological motion compensation

Controlling the interaction between robots and living soft tissues has become an important issue as the number of robotic systems inside the operating room increases. Many researches have been done on force control to help surgeons during medical procedures, such as physiological motion compensation and tele-operation systems with haptic feedback. In order to increase the performance of such controllers, this work presents a novel force control scheme using Active Observer (AOB) based on a viscoelastic interaction model. The control scheme has shown to be stable through theoretical analysis and its performance was evaluated by in vitro experiments. In order to evaluate how the force control scheme behaves under the presence of physiological motion, experiments considering breathing and beating heart disturbances are presented. The proposed control scheme presented a stable behavior in both static and moving environment. The viscoelastic AOB presented a compensation ratio of 87% for the breathing motion and 79% for the beating heart motion.     

Design and control of a novel variable stiffness soft arm

Soft robot arms possess such characteristics as light weight, simple structure and good adaptability to the environment, among others. On the other hand, robust control of soft robot arms presents many difficulties. Based on these reasons, this paper presents a novel design and modeling of a fuzzy active disturbance rejection control (FADRC) controller for a soft PAM arm. The soft arm comprises three contractile and one extensor PAMs, which can vary its stiffness independently of its position in space. Force analysis for the soft arm is conducted, and stiffness model of the arm is established based on the relational model of contractile and extensor PAM. The accuracy of stiffness model for the soft arm was verified through experiments. Associated to this, a controller based on the fuzzy adaptive theory and active disturbance rejection control (ADRC), FADRC, has been designed to control the arm. The fuzzy adaptive theory is used to adjust the parameters of the ADRC, the control algorithm has the ability to control stiffness and position of the soft arm. In this paper, FADRC was further verified through comparative experiments on the soft arm. This paper reinforces the hypothesis that FADRC control, as an algorithm, indeed possesses good robustness and adaptive abilities.     

Contribution to the indirect decentralized adaptive control of manipulation robots

In this paper, efficient approaches to the synthesis of indirect decentralized adaptive control for manipulation robots are presented. The first part of control synthesis consists of the estimation of unknown dynamic robot parameters using the methods of recursive identification and fast dynamic as well as identification models in a symbolic form. The second part of synthesis includes the self-tuning control strategy which is a basis for adaptive control synthesis according to the estimates of the unknown dynamic parameters. Using the theory of decentralized systems, a new robust algorithm for adaptive control with the ability of adaptation in the feedforward or feedback loop are proposed. A complete stability and convergence analysis is presented. A special part of the paper represents an analysis of practical implementation of the proposed control algorithms on modern microprocessor-based robot controllers. Based on this analysis, an efficient application of indirect adaptive algorithms in real time with high-quality system performance is shown. Adaptive algorithms are verified through simulation of trajectory tracking for an industrial robot with unknown dynamic parameters of payload.     

基于声波操纵的微小物体运动建模与控制

采用声波操纵克拉尼平板上的微小物体, 在精准医学、液滴和颗粒的工业控制等方面有着广阔的应用前景. 传统声波操纵认为在运动过程中, 声波对微粒的影响是无序的, 而近年来, 研究得出声振动是有序的, 但缺乏精确、有效的建模手段, 限制其应用. 针对该问题, 本文提出了结合Faster R-CNN算法与局部加权回归(LOESS)算法的方法对声波场进行建模. 采用图像识别技术辨识微粒在克拉尼平板上的位置, 计算在某一固定声波频率下微小粒子在克拉尼平板不同位置上的位移. 在积累大量位移数据后, 基于LOESS算法, 建立平板上的完整声波位移模型,分析声波力场如何在平面上对微小物体的运动施加影响, 并建立仿真模型, 进行克拉尼平板上微粒操纵的仿真实验. 最后, 本文将基于所搭建的声波操纵平台, 对易碎的速溶咖啡颗粒进行控制, 通过与仿真实验相对比, 验证了建模与控制方法的可行性, 证明该模型可实现微小粒子的运动控制.     

某雷达系统中伪码对齐的滑动控制方法及FPGA实现

本文主要阐述了在某雷达系统中为实现伪码对齐．所采用的滑动控制方法的原理及在FPGA芯片上的实现。     

Fuzzy sliding mode control of a finger of a humanoid robot hand

Abstract: The motion control problem for the finger of a humanoid robot hand is investigated. First, the index finger of the human hand is dynamically modelled as a kinematic chain of cylindrical links. During construction of the model, special attention is given to determining bone dimensions and masses that are similar to the real human hand. After the kinematic and dynamic analysis of the model, in order to ensure that the finger model tracks its desired trajectory during a closing motion, a fuzzy sliding mode controller is applied to the finger model. In this controller, a fuzzy logic algorithm is used in order to tune the control gain of the sliding mode controller; thus, an adaptive controller is obtained. Finally, numerical results, which include a performance comparison of the proposed fuzzy sliding mode controller and a conventional sliding mode controller, are presented. The results demonstrate that the proposed control method can be used to perform the desired motion task for humanoid robot hands efficiently.     

语义特征建模系统中操作局部化的研究

为了提高语义特征建模系统约束求解的效率及系统的整体性能,提出了一种新的操作局部化方法。该方法使用特征语义表示法来描述产品模型中特征的各种信息,改进了细胞元模型对特征元素的管理机制,通过特征的“语义面”将局部特征从模型中有效地分离出来,通过创建临时特征的方法来实现模型的局部约束求解。该策略不仅可以完全满足在复杂模型中直接操作的需要,还可以大大提高系统的性能。实验表明该算法具有更强的适应性和实用性。