Dynamic visual servo control of a 4-axis joint tool to track image trajectories during machining complex shapes

A large part of the new generation of computer numerical control systems has adopted an architecture based on robotic systems. This architecture improves the implementation of many manufacturing processes in terms of flexibility, efficiency, accuracy and velocity. This paper presents a 4-axis robot tool based on a joint structure whose primary use is to perform complex machining shapes in some non-contact processes. A new dynamic visual controller is proposed in order to control the 4-axis joint structure, where image information is used in the control loop to guide the robot tool in the machining task. In addition, this controller eliminates the chaotic joint behavior which appears during tracking of the quasi-repetitive trajectories required in machining processes. Moreover, this robot tool can be coupled to a manipulator robot in order to form a multi-robot platform for complex manufacturing tasks. Therefore, the robot tool could perform a machining task using a piece grasped from the workspace by a manipulator robot. This manipulator robot could be guided by using visual information given by the robot tool, thereby obtaining an intelligent multi-robot platform controlled by only one camera.     

微操作机器人的视觉伺服控制

视觉伺服控制是微操作机器人实现精确运动,完成自动操作的必要手段．本文介绍 了实现微操作机器人视觉伺服控制的方法．首先论述了微操作机器人的视觉伺服结构,并以 建立的面向生物工程的双手微操作机器人系统为例,介绍了基于二维显微视觉信息的三自由 度柔性铰链微操作机器人的运动学建模方法,针对压电驱动器控制器的特点提出了基本的PI D视觉伺服控制规律实现方法,并进行了点到点运动和圆轨迹跟踪实验．实验结果表明,视 觉伺服控制克服了由于标定以及环境等因素导致的运动模型不准确而引入的误差．     

Implementation of real-time distributed control for discrete event robotic systems using Petri nets

This article presents a systematic method of modeling and implementing real-time control for discrete-event robotic systems using Petri nets. Because, in complex robotic systems such as flexible manufacturing systems, the controllers are distributed according to their physical structure, it is desirable to realize real-time distributed control. In this article, the task specification of robotic processes is represented as a system control-level net. Then, based on the hierarchical approach, it is transformed into detailed subnets, which are decomposed and distributed into the local machine controllers. The implementation of real-time distributed control through communication between the system controller and the machine controllers on a microcomputer network is described for a sample robotic system. The proposed implementation method is sufficiently general, and can be used as an effective prototyping tool for consistent modeling, simulation, and real-time control of large and complex robotic systems.     

机器人视觉伺服研究进展:视觉系统与控制策略

视觉伺服控制是机器人系统的重要控制手段. 随着机器人应用需求的日益复杂多样,视觉伺服的研究面临着挑战. 视觉伺服系统的设计主要包括视觉系统、控制策略和实现策略三个方面. 文中对视觉伺服中存在的主要问题进行了分析,重点介绍了视觉系统中改善动态性能和处理噪声的主要技术手段,阐述了处理模型不确定性和约束的控制策略的改进方案,总结了提高视觉伺服系统的可实现性和灵活性的实现策略. 最后,基于当前的研究进展对未来的研究方向进行了展望.     

Agent-based control for fuzzy behavior programming in robotic excavation

This paper discusses the concept, formulation, and implementation of the agent-based control for fuzzy behavior programming in robotic excavation. Petri net transducers are introduced to describe excavation control agent coordination and specification, while fuzzy control rules are used to implement primitive motions. A prototype laboratory excavation system is built with PUMA robotic manipulators and a force/torque sensor. Extensive experiments have been conducted and the results have demonstrated that the proposed control method is capable of continuously adapting and replanning its actions based on sensory feedback, and completing its excavation tasks in dynamic and unstructured environments.     

Information based indoor environment robotic exploration and modeling using 2-D images and graphs

As the autonomy of personal service robotic systems increases so has their need to interact with their environment. The most basic interaction a robotic agent may have with its environment is to sense and navigate through it. For many applications it is not usually practical to provide robots in advance with valid geometric models of their environment. The robot will need to create these models by moving around and sensing the environment, while minimizing the complexity of the required sensing hardware. Here, an information-based iterative algorithm is proposed to plan the robot's visual exploration strategy, enabling it to most efficiently build a graph model of its environment. The algorithm is based on determining the information present in sub-regions of a 2-D panoramic image of the environment from the robot's current location using a single camera fixed on the mobile robot. Using a metric based on Shannon's information theory, the algorithm determines potential locations of nodes from which to further image the environment. Using a feature tracking process, the algorithm helps navigate the robot to each new node, where the imaging process is repeated. A Mellin transform and tracking process is used to guide the robot back to a previous node. This imaging, evaluation, branching and retracing its steps continues until the robot has mapped the environment to a pre-specified level of detail. The set of nodes and the images taken at each node are combined into a graph to model the environment. By tracing its path from node to node, a service robot can navigate around its environment. This method is particularly well suited for flat-floored environments. Experimental results show the effectiveness of this algorithm.     

Image-based robot task planning and control using a compact visualrepresentation

We present an approach for the design and control of both reflexive and purposive visual tasks. The approach is based on the bidimensional appearance of the objects in the environment and explicitly takes into account independent object motions. A linear model of camera-object interaction is embedded in the control scheme, which dramatically simplifies visual analysis and control by reducing the size of visual representation. We describe the implementation of three visual tasks of increasing complexity, obtained with the proposed scheme and based on the active contour analysis and polynomial planning of image contour transformations. Both simulations and real-time experiments with a robotic eye-in-hand configuration are discussed, validating the approach in terms of robustness and applicability to visual navigation, active exploration and perception, and human-robot interaction     

The AutoSOAR autonomous soaring aircraft,part 1: Autonomy algorithms

Autonomous soaring has the potential to greatly improve both the range and endurance of small robotic aircraft. This paper describes an autonomous soaring system that generates a dynamic map of lift sources (thermals) in the environment and uses this map for online flight planning and decision making. Components of the autonomy algorithm include thermal mapping, explore/exploit decision making, navigation, optimal airspeed computation, thermal centering control, and energy state estimation. A finite state machine manages the aircraft behavior during flight and determines when changing behavior is appropriate. A complete system to enable autonomous soaring is described with special attention paid to practical considerations encountered during flight testing. A companion paper describes the hardware implementation of this system and the results of a flight test campaign conducted at Aberdeen Proving Ground in September 2015.     

Knowledge graph and function block based Digital Twin modeling for robotic machining of large-scale components

Robotic machining is a potential method for machining large-scale components (LSCs) due to its low cost and high flexibility. However, the low stiffness of robots and complex machining process of LSCs result in a lack of alignment between the physical process and digital models, making it difficult to realize the robotic machining of LSCs. The recent Digital Twin (DT) concept shows potential in terms of representing and modeling physical processes. Therefore, this study proposes a robotic machining DT for LSCs. However, the current DT is not capable of knowledge representation, multi-source data integration, optimization algorithm implementation, and real-time control. To address these issues, Knowledge Graph (KG) and Function Block (FB) are employed in the proposed robotic machining DT. Here, robotic machining related information, such as the machining parameters and errors, is represented in the virtual space by building the KG, whereas the FBs are responsible for integrating and applying the algorithms for process execution and optimization based on real-world events. Moreover, a novel adaptive process adjustment strategy is proposed to improve the efficiency of the process execution. Finally, a prototype system of the robotic machining DT is developed and validated by an experiment on robotic milling of the assembly interface for an LSC. The results demonstrate that the robotic machining is successfully optimized and improved by the proposed method.     

基于激光雷达与双目视觉的移动机器人SLAM研究

为解决移动机器人在环境未知条件下,利用单一传感器自主导航时不能及时定位、构建地图不精确的问题,提出采用一种改进RBPF算法,在计算提议分布时将移动机器人的观测数据(视觉信息与激光雷达信息)和里程计信息融合;针对一般视觉图像特征点提取算法较慢的问题,采用基于ORB算法对视觉图像进行处理以加快视觉图像处理速度的方法;最后通过在安装有开源机器人操作系统(ROS)的履带式移动机器人进行实验,验证了采用该方法可构建可靠性更高、更精确的2D栅格图,提高了移动机器人SLAM的鲁棒性.     

无人飞艇的基于计算机视觉导航和预设航线跟踪控制

小型无人飞艇在反恐防暴、灾难监控、大气监测、广告、航拍、交通监控、应急通信中继平台等很多方面都有广阔的应用前景.这些应用都要求飞艇具有自动跟踪预设航线的能力.因此，本文提出了基于计算机视觉导航和优化模糊控制的策略来实现预设航线的自动跟踪.文中首先详细介绍了基于自然标志的视觉导航原理，无人飞艇机载视觉系统通过跟踪这些特征点——易在图像处理中识别的自然标志，例如城市中的高层建筑物，再结合数字地图或GIS，获取它们的位置和几何特征信息，利用针孔模型成像的几何关系解算出飞艇的位置和方向；接着根据无人飞艇的动力学特性，设计了以视觉导航获取的飞艇位置和方向信息作为输入的模糊飞控系统，并用GA算法优化了模糊控制器的成员关系函数.最后进行了验证和分析.     

Real-time implementation of a robust adaptive controller for arobotic manipulator based on digital signal processors

Presents an approach to the design and real-time implementation of an adaptive controller for a robotic manipulator based on digital signal processors. The Texas Instruments DSP (TMS320C31) chips are used in implementing real-time adaptive control algorithms to provide enhanced motion control performance for robotic manipulators. In the proposed scheme, adaptation laws are derived from the direct model reference adaptive control principle based on the improved Lyapunov second method. The proposed adaptive controller consists of an adaptive feedforward and feedback controller and PI-type time-varying auxiliary control elements. The proposed control scheme is simple in structure, fast in computation, and suitable for real-time control. Moreover, this scheme does not require any accurate dynamic modeling nor values of manipulator parameters and payload. Performance of the proposed adaptive controller is illustrated by simulation and experimental results for an industrial robot with four joints in the joint space and Cartesian space     

机器人相机空间智能编程方法研究*

针对传统的示教编程方式存在操作复杂,效率低,危险性高等不足,严重限制了工业机器人的推广应用。基于自然的人机交互示教方式,提出了一种基于计算机视觉的相机空间工业机器人智能虚拟编程方法,本方法不需要实际操作示教盒和机器人本体,仅采用辅助示教工具在视觉相机空间示教就实现了工业机器人的虚拟编程。主要研究了实现该方案的关键技术即基于相机空间映射模型的视觉定位技术以及基于K-means聚类算法实现的相机空间映射关系自学习技术。最后,基于自主开发的机器人平台,开展基于相机空间的虚拟智能编程实验,验证了本文提出的相机空间工业机器人智能编程方法的可行性及正确性。     

Soft object deformation monitoring and learning for model-based robotic hand manipulation

This paper discusses the design and implementation of a framework that automatically extracts and monitors the shape deformations of soft objects from a video sequence and maps them with force measurements with the goal of providing the necessary information to the controller of a robotic hand to ensure safe model-based deformable object manipulation. Measurements corresponding to the interaction force at the level of the fingertips and to the position of the fingertips of a three-finger robotic hand are associated with the contours of a deformed object tracked in a series of images using neural-network approaches. The resulting model captures the behavior of the object and is able to predict its behavior for previously unseen interactions without any assumption on the object's material. The availability of such models can contribute to the improvement of a robotic hand controller, therefore allowing more accurate and stable grasp while providing more elaborate manipulation capabilities for deformable objects. Experiments performed for different objects, made of various materials, reveal that the method accurately captures and predicts the object's shape deformation while the object is submitted to external forces applied by the robot fingers. The proposed method is also fast and insensitive to severe contour deformations, as well as to smooth changes in lighting, contrast, and background.     

Dependable Low‐altitude Obstacle Avoidance for Robotic Helicopters Operating in Rural Areas

This paper presents a system enabling robotic helicopters to fly safely without user interaction at low altitude over unknown terrain with static obstacles. The system includes a novel reactive behavior‐based method that guides rotorcraft reliably to specified locations in sparsely occupied environments. System dependability is, among other things, achieved by utilizing proven system components in a component‐based design and incorporating safety margins and safety modes. Obstacle and terrain detection is based on a vertically mounted off‐the‐shelf two‐dimensional LIDAR system. We introduce two flight modes, pirouette descent and waggle cruise, which extend the field of view of the sensor by yawing the aircraft. The two flight modes ensure that all obstacles above a minimum size are detected in the direction of travel. The proposed system is designed for robotic helicopters with velocity and yaw control inputs and a navigation system that provides position, velocity, and attitude information. It is cost effective and can be easily implemented on a variety of helicopters of different sizes. We provide sufficient detail to facilitate the implementation on single‐rotor helicopters with a rotor diameter of approximately 1.8 m. The system was extensively flight‐tested in different real‐world scenarios in Queensland, Australia. The tests included flights beyond visual range without a backup pilot. Experimental results show that it is feasible to perform dependable autonomous flight using simple but effective methods. © 2013 Wiley Periodicals, Inc.     

Collision Detection and Safe Reaction Algorithm for Non-backdrivable Manipulator with Single Force/Torque Sensor

The paper presents a robust control law for homing of an autonomous robot. The proposed work aims to solve this problem for practical conditions such as random errors in commanded velocities and unknown distance sensor characteristics. The proposed steering control aligns the robot’s orientation with homing vector using arbitrary real valued distance function providing the capability to work in changing environment conditions. Finite time convergence to the equilibrium using proposed control law is achieved in the presence of bounded random velocity errors regardless of the initial position and orientation. Just the sign information as feedback supports applicability of proposed control law with any distance function. A matching parameter between panoramic images obtained at home and current positions is a function of distance between home and current positions. However, explicit relation between distance and image matching parameter is unknown. This work demonstrates the application of proposed method for visual homing based on image distance function rendering the benefit of minimal image processing. Various simulation and experimental results are presented for visual homing to support the theory presented in this paper. Advantage of proposed visual homing is also explored in changing environment conditions.     

Uncalibrated Eye-to-Hand Visual Servoing Using Inverse Fuzzy Models

A new uncalibrated eye-to-hand visual servoing based on inverse fuzzy modeling is proposed in this paper. In classical visual servoing, the Jacobian plays a decisive role in the convergence of the controller, as its analytical model depends on the selected image features. This Jacobian must also be inverted online. Fuzzy modeling is applied to obtain an inverse model of the mapping between image feature variations and joint velocities. This approach is independent from the robot's kinematic model or camera calibration and also avoids the necessity of inverting the Jacobian online. An inverse model is identified for the robot workspace, using measurement data of a robotic manipulator. This inverse model is directly used as a controller. The inverse fuzzy control scheme is applied to a robotic manipulator performing visual servoing for random positioning in the robot workspace. The obtained experimental results show the effectiveness of the proposed control scheme. The fuzzy controller can position the robotic manipulator at any point in the workspace with better accuracy than the classic visual servoing approach.     

Extended active observer for force estimation and disturbance rejection of robotic manipulators

The current control methods applied to robotic manipulators either require full state and force measurements, or use the state and force estimation in the absence of any kind of disturbance. As an alternative approach, a new adaptive motion control approach for robotic manipulators extending the existing active observer for simultaneous inertial parameters and force estimation is proposed. The scheme provides accurate force and full state estimation in the presence of robot inertial parameter variations and measurement noise, both subsequently used in the design of a controller. Since the proposed method relies mainly on the position of the plant, it significantly reduces the difficulty and cost of implementation. The velocity, parameter and force signals are estimated from the position. The approach is applied to a typical two-degree-of-freedom (2DOF) robotic manipulator through computer simulation. The results are encouraging and demonstrate the noise rejection ability of the scheme.     

在人机协作中基于动量观测和优化算法的全机械臂单点接触信息实时估计

针对协作型机器人,提出了一种依据机器人控制与运动状态信息,基于动量观测与优化算法相结合的全机械臂单点接触信息实时估计方法.该方法将接触位置估计问题转化为优化算法有界搜索问题,搜索范围由动量观测方法确定的接触臂长度确定,两种方法的结合保证了估计的精度和实时性.基于UR机械臂实验平台的仿真与实验结果表明,本文方法能够实时、准确地估计除第1关节以外首次发生接触的机械臂任意位置处的力和位置信息.本研究可以在不借助传感器的情况下实现机械臂对外力的感知.