Three-dimensional positioning control based on stereo microscopic visual servoing system

The design of domestic drying oven lacked theoretical basis and methods, especially a tool supporting experiments and verifying the results of theoretical research. This paper developed a platform, which can be used to automatically detect multi-point air temperature and wind speed from drying oven nozzle of printing and coating machines. The hardware design of platform achieves a four-axis positioning function by adopt a three-dimensional Cartesian coordinate robot and an additional servo motor. The LabVIEW-based software design of platform achieves many functions, including multi-axis positioning control, data acquisition and processing, data interface and operation interface. This platform contributes to research work for drying oven.

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3-D positioning control by linear visual servoing

Artificial Life and Robotics ◽

10.1007/bf02480882 ◽

2003 ◽

Vol 7 (1-2) ◽

pp. 28-31 ◽

Cited By ~ 2

Author(s):

K. Namba ◽

N. Maru

Keyword(s):

Visual Servoing ◽

Positioning Control

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Positioning control of the leg of the humanoid robot by linear visual servoing

4th IEEE/RAS International Conference on Humanoid Robots, 2004. ◽

10.1109/ichr.2004.1442110 ◽

2005 ◽

Cited By ~ 2

Author(s):

Y. Yamamura ◽

N. Maru

Keyword(s):

Visual Servoing ◽

Humanoid Robot ◽

Positioning Control

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Design and Evaluation of Human–Machine Interface for NEXUS: A Custom Microassembly System

Journal of Micro and Nano-Manufacturing ◽

10.1115/1.4049667 ◽

2020 ◽

Vol 8 (4) ◽

Author(s):

Danming Wei ◽

Mariah B. Hall ◽

Andriy Sherehiy ◽

Dan O. Popa

Keyword(s):

Visual Servoing ◽

Degrees Of Freedom ◽

Three Dimensional ◽

Human Machine Interface ◽

Mems Technology ◽

Machine Interface ◽

Micro Electromechanical System ◽

Performance Results ◽

Assembly Performance ◽

Assembly Rate

Abstract Microassembly systems utilizing precision robotics have long been used for realizing three-dimensional microstructures such as microsystems and microrobots. Prior to assembly, microscale components are fabricated using micro-electromechanical-system (MEMS) technology. The microassembly system then directs a microgripper through a series of automated or human-controlled pick-and-place operations. In this paper, we describe a novel custom microassembly system, named NEXUS, that can be used to prototype MEMS microrobots. The NEXUS integrates multi-degrees-of-freedom (DOF) precision positioners, microscope computer vision, and microscale process tools such as a microgripper and vacuum tip. A semi-autonomous human–machine interface (HMI) was programmed to allow the operator to interact with the microassembly system. The NEXUS human–machine interface includes multiple functions, such as positioning, target detection, visual servoing, and inspection. The microassembly system's HMI was used by operators to assemble various three-dimensional microrobots such as the Solarpede, a novel light-powered stick-and-slip mobile microcrawler. Experimental results are reported in this paper to evaluate the system's semi-autonomous capabilities in terms of assembly rate and yield and compare them to purely teleoperated assembly performance. Results show that the semi-automated capabilities of the microassembly system's HMI offer a more consistent assembly rate of microrobot components and are less reliant on the operator's experience and skill.

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Rapid satellite capture by a space robot based on delay compensation

Industrial Robot the international journal of robotics research and application ◽

10.1108/ir-07-2016-0193 ◽

2017 ◽

Vol 44 (3) ◽

pp. 363-376 ◽

Cited By ~ 4

Author(s):

Zhenyu Li ◽

Bin Wang ◽

Haitao Yang ◽

Hong Liu

Keyword(s):

Time Delay ◽

Visual Servoing ◽

Error Control ◽

Three Dimensional ◽

Experimental System ◽

Space Robot ◽

Robot Kinematics ◽

Delay Compensation ◽

Content Type ◽

Satellite Capture

Purpose Rapid satellite capture by a free-floating space robot is a challenge problem because of no-fixed base and time-delay issues. This paper aims to present a modified target capturing control scheme for improving the control performance. Design/methodology/approach For handling such control problem including time delay, the modified scheme is achieved by adding a delay calibration algorithm into the visual servoing loop. To identify end-effector motions in real time, a motion predictor is developed by partly linearizing the space robot kinematics equation. By this approach, only ground-fixed robot kinematics are involved in the predicting computation excluding the complex space robot kinematics calculations. With the newly developed predictor, a delay compensator is designed to take error control into account. For determining the compensation parameters, the asymptotic stability condition of the proposed compensation algorithm is also presented. Findings The proposed method is conducted by a credible three-dimensional ground experimental system, and the experimental results illustrate the effectiveness of the proposed method. Practical implications Because the delayed camera signals are compensated with only ground-fixed robot kinematics, this proposed satellite capturing scheme is particularly suitable for commercial on-orbit services with cheaper on-board computers. Originality/value This paper is original as an attempt trying to compensate the time delay by taking both space robot motion predictions and compensation error control into consideration and is valuable for rapid and accurate satellite capture tasks.

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Robust Motion Generation for Vision-Guided Robot Bin-Picking

Volume 9: Mechanical Systems and Control, Parts A, B, and C ◽

10.1115/imece2007-42606 ◽

2007 ◽

Cited By ~ 3

Author(s):

Simon Leonard ◽

Ambrose Chan ◽

Elizabeth Croft ◽

James J. Little

Keyword(s):

Visual Servoing ◽

Industrial Robot ◽

Three Dimensional ◽

Cost Effective ◽

Object Localization ◽

Assembly Lines ◽

Motion Generation ◽

Simple Task ◽

Bin Picking ◽

Modern Manufacturing

This paper discusses work towards a vision-based solution to the problem of robot bin-picking. The problem of robot bin-picking is defined as searching for and recognizing a part among many lying jumbled in a bin such that the robot is able to grasp and manipulate the part. Despite decades of research in vision, robotics, and manufacturing, this problem remains open. Currently, in modern manufacturing, this seemingly simple task is performed by complex assembly lines or manual labor. The amount of efforts and costs associated with the current solutions to bin-picking is a testament to the importance of a new solution. The main objective of this research is a reliable and cost effective automated solution to the bin-picking problem encountered in manufacturing. As a broader contribution, this research also provides a robust visual servoing method that enables safe interactions between a robot and its environment. Our system uses visual feedback to generate tasks autonomously and to control the interaction of the manipulator with its environment. First, our system relies on robust vision-based object localization to generate three-dimensional pose hypotheses for each identified part. Then, the hypotheses are filtered according to the feasibility of their picking configuration. Finally, a trajectory is generated for a picking position. In this paper, we consider the specifications of the trajectory ensure that collisions with the bin and joints limits are avoided, while servoing the robot to the part. To ensure the reliability of the system, the procedure is tested in a simulation before being executed by a manipulator. Our experiments target the automotive industry and involve real engine parts a typical industrial robot and metal bin.

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Optimized hybrid decoupled visual servoing with supervised learning

Proceedings of the Institution of Mechanical Engineers Part I Journal of Systems and Control Engineering ◽

10.1177/09596518211028379 ◽

2021 ◽

pp. 095965182110283

Author(s):

Alireza Rastegarpanah ◽

Ali Aflakian ◽

Rustam Stolkin

Keyword(s):

Linear Model ◽

Visual Servoing ◽

Three Dimensional ◽

Interaction Matrix ◽

Two Dimensional ◽

Model Tree ◽

Local Linear ◽

Neuro Fuzzy ◽

Fuzzy Neural ◽

Classical Image

This study proposes an optimized hybrid visual servoing approach to overcome the imperfections of classical two-dimensional, three-dimensional and hybrid visual servoing methods. These imperfections are mostly convergence issues, non-optimized trajectories, expensive calculations and singularities. The proposed method provides more efficient optimized trajectories with shorter camera path for the robot than image-based and classical hybrid visual servoing methods. Moreover, it is less likely to lose the object from the camera field of view, and it is more robust to camera calibration than the classical position-based and hybrid visual servoing methods. The drawbacks in two-dimensional visual servoing are mostly related to the camera retreat and rotational motions. To tackle these drawbacks, rotations and translations in Z-axis have been separately controlled from three-dimensional estimation of the visual features. The pseudo-inverse of the proposed interaction matrix is approximated by a neuro-fuzzy neural network called local linear model tree. Using local linear model tree, the controller avoids the singularities and ill-conditioning of the proposed interaction matrix and makes it robust to image noises and camera parameters. The proposed method has been compared with classical image-based, position-based and hybrid visual servoing methods, both in simulation and in the real world using a 7-degree-of-freedom arm robot.

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