Yongfei Xiao

Bio: Yongfei Xiao is an academic researcher from Chinese Academy of Sciences. The author has contributed to research in topics: Computer science & Robot. The author has an hindex of 4, co-authored 6 publications receiving 41 citations.

A combined 2D-3D vision system for automatic robot picking

Abstract: This paper presents a new vision technique for an industrial robot to pick up randomly placed workpieces. The proposed approach combines 2D and 3D vision for efficiently determining the spatial position of a target object in cluttered scenes. 2D vision permits to quickly detect and locate objects of interest, thus reducing significantly the processing time. The location of an extracted 2D region (a detected object) is then passed to the 3D vision module to determine its world coordinate. Finally the 3D position information is sent to the robot manipulator for automatic picking. The test results show the effectiveness of the proposed system.

A shape-based stereo matching algorithm for binocular vision

Abstract: Binocular stereo vision is an important branch of the research area in computer vision. Stereo matching is the most important process in binocular vision. In this paper, a new stereo matching scheme using shape-based matching (SBM) is presented to improve the depth reconstruction method of binocular stereo vision systems. The method works in two steps. First, an operator registers the pattern including the key features of an object to be measured. Then during the operation stage, the stereo camera snaps stereo images and finds the patterns in right and left images separately by means of the SBM. The 3D positions of the object are calculated by using the corresponding points of the stereo images and the projection matrices of the stereo camera. Since we apply robust image processing algorithms, such as the SBM, the proposed method becomes more reliable than the conventional stereo vision systems.

An automatic robot unstacking system based on binocular stereo vision

Abstract: Unstacking is a process widely used in many industrial applications. This paper proposes an automatic unstacking system using an industrial robot and stereo vision. To detect a package to be picked, a shape-based matching (SBM) method is applied on 2D images. The 3D position of a selected package among pick-up candidates is calculated by acquiring a pair of correspondence points in the left and right images of a binocular camera. In order to improve the 3D pose estimation performance, the SBM method is also used instead of the conventional stereo matching method. Since SBM is a robust image processing algorithm, the proposed vision system can be employed for various general-purpose applications. Furthermore an unstacking strategy, in which the robot automatically picks packages in each layer of the stack, is established. Experimental results on a stack of commercial packages validated the 3D positioning accuracy of the vision system and the robot successfully manipulates the stacked packages.

Design and grip force control of dual-motor drive electric gripper with parallel fingers

Abstract: This paper designs a novel electric gripper with parallel fingers and each finger has a set of an independent drive motor and integrates a force sensor. The gripper with the flexibility of mechanical structure and control is mounted in the end of an industrial robot, and a flexible grip test platform is constructed based on an embedded controller. Prarllel position-force control algorithm is proposed to be used for the gripper, and dual fingers can be individually position-controlled or force-controlled. The grip force, position and speed can be set individually so that the clamping centre and strokes can be programmed to control with improved dexterity. It can make the resulting grip force rapidly track desired force with low overshoots to a tolerable limit and be quickly stabilized within an acceptable range. Robots grip experiments show that the gripper can provide flexible grip, improve the flexibility and reduce damages to the fragile and deformable objects during dynamic grip process.

PSO versus GAs for fast object localization problem

Abstract: Particle swarm optimization (PSO) and genetic algorithms (GAs) are two kinds of widely used evolutionary compution techniques. In this paper, a particle swarm optimizer is implemented and compared to a genetic algorithm for the object localization problem. The problem of object localization can be formulated into an integer nonlinear optimization problem (INOP). We respectively expand the basic PSO and GA to solve the formulated INOP. Experiments were made on a set of 42 test images with complex backgrounds. The results show that although GA and PSO share many common features, PSO is more suitable for the problem than GA.

A Comparative Review of Hand-Eye Calibration Techniques for Vision Guided Robots

Abstract: Hand-eye calibration enables proper perception of the environment in which a vision guided robot operates. Additionally, it enables the mapping of the scene in the robots frame. Proper hand-eye calibration is crucial when sub-millimetre perceptual accuracy is needed. For example, in robot assisted surgery, a poorly calibrated robot would cause damage to surrounding vital tissues and organs, endangering the life of a patient. A lot of research has gone into ways of accurately calibrating the hand-eye system of a robot with different levels of success, challenges, resource requirements and complexities. As such, academics and industrial practitioners are faced with the challenge of choosing which algorithm meets the implementation requirements based on the identified constraints. This review aims to give a general overview of the strengths and weaknesses of different hand-eye calibration algorithms available to academics and industrial practitioners to make an informed design decision, as well as incite possible areas of research based on the identified challenges. We also discuss different calibration targets, which is an important part of the calibration process that is often overlooked in the design process.

Adaptive Variable Parameter Impedance Control for Apple Harvesting Robot Compliant Picking

Abstract: In order to reduce the damage of apple harvesting robot to fruits and achieve compliant picking, an adaptive variable parameter impedance control method for apple harvesting robot compliant picking is proposed in this paper. Firstly, the Burgers viscoelastic model is used to characterize the rheological properties of apples and study the variation of mechanical properties of apple grasping at different speeds. Then, a force-based impedance control system is designed. On this basis, aiming at the influence of impedance controller parameters on contact force, three impedance parameters self-tuning functions are constructed to complete the design of an improved force-based impedance control system based on the hyperbolic secant function. The simulation and experimental results show that the proposed control makes the desired force smoother, and its overshoot is about 2.3%. The response speed is faster, and the adjustment time of contact force is shorter of about 0.48 s. The contact force overshoot is about 2%, which is 37.5% less than that of the traditional force-based impedance control. This research improves the control performance for apple harvesting robot compliant picking.

Robot unstacking method based on binocular stereoscopic vision

Abstract: The invention discloses a robot unstacking method based on binocular stereoscopic vision. The robot unstacking method includes the following steps of: simultaneously obtaining images within views of left and right eyes by using a binocular camera fixed right above a working area, and positioning a target by using a shape template matching method to obtain a three-dimensional coordinate under the camera coordinate system; converting from the camera coordinate system into a robot base coordinate system; arranging depth information and unstacking in a layered manner according to the detected target coordinate. According to the robot unstacking method based on binocular stereoscopic vision, target identification and three-dimensional positioning of product in an unstacking area are achieved directly through collecting binocular images, and thereby automatic unstacking task of the product is achieved, and the problems that manual unstacking is large in labor intensity and low in efficiency can be effectively overcome.

A Workpiece Localization Method for Robotic De-Palletizing Based on Region Growing and PPHT

Abstract: Aiming at the problem that the robot de-palletizing task is difficult to accomplish under unstable ambient light, a two-step method is proposed to realize the localization of workpieces, which in this work are woven bags. To begin with, Region Growing method is used to extract the whole target region in the original image, and the relationship model between image intensity and the optimal Region Growing threshold is established. Then, Progressive Probabilistic Hough Transform(PPHT) is used to locate each woven bag. To improve the system performance, the optimal parameters of the PPHT function in different illumination intervals are determined. Finally, experiments are conducted to verify the effectiveness of the proposed method. Experiment results demonstrate this method is robust and feasible.

How to achieve precise operation of a robotic manipulator on a macro to micro/nano scale

Abstract: Purpose The purpose of this paper is to present state-of-the-art approaches for precise operation of a robotic manipulator on a macro- to micro/nanoscale. Design/methodology/approach This paper first briefly discussed fundamental issues associated with precise operation of a robotic manipulator on a macro- to micro/nanoscale. Second, this paper described and compared the characteristics of basic components (i.e. mechanical parts, actuators, sensors and control algorithm) of the robotic manipulator. Specifically, commonly used mechanisms of the manipulator were classified and analyzed. In addition, intuitive meaning and applications of its actuator explained and compared in details. Moreover, related research studies on general control algorithm and visual control that are used in a robotic manipulator to achieve precise operation have also been discussed. Findings Remarkable achievements in dexterous mechanical design, excellent actuators, accurate perception, optimized control algorithms, etc., have been made in precise operations of a robotic manipulator. Precise operation is critical for dealing with objects which need to be manufactured, modified and assembled. The operational accuracy is directly affected by the performance of mechanical design, actuators, sensors and control algorithms. Therefore, this paper provides a categorization showing the fundamental concepts and applications of these characteristics. Originality/value This paper presents a categorization of the mechanical design, actuators, sensors and control algorithms of robotic manipulators in the macro- to micro/nanofield for precise operation.