The Experts below are selected from a list of 154239804 Experts worldwide ranked by ideXlab platform

Yuchen Wang - One of the best experts on this subject based on the ideXlab platform.

  • contact force torque prediction and analysis model for large length diameter ratio peg in hole assembly
    Robotics and Biomimetics, 2018
    Co-Authors: Yuchen Wang, Zhao Xiong, Xusong Quan, Xiaodong Yuan, Peng Wang, Hai Zhou
    Abstract:

    Large length-diameter ratio Peg-in-Hole assembly is a hard and significant issue in modern industry. The prediction and control of the contact force/torque play a crucial part in flexible assembly. They ensure that the contact force/torque data are within limits in assembly process, which can prevent jam and protect devices. In this paper, we propose a novel contact force/torque prediction and analysis model to solve the large length-diameter ratio Peg-in-Hole assembly problem in which the contact states are difficult to be obtained. Firstly, we establish a new force/torque prediction model with measured data to obtain the precision actual contact force/torque which is critical for assembly control. Then, a new contact analysis model for large length-diameter ratio Peg-in-Hole assembly is built to estimate the assembly contact states. At last, based on the proposed contact force/torque prediction and analysis model, we design a robot pose adjustment strategy for large length-diameter ratio Peg-in-Hole assembly. Experiment results demonstrate that the proposed model can meet the demands of large length-diameter ratio Peg-in-Hole assembly. The predicted error rates of force/torque are lower than 1 % and the mean force/torque in assembly process are lower than 5 N / 0.5 N.m by our model.

  • ROBIO - Contact Force/Torque Prediction and Analysis Model for Large Length-diameter Ratio Peg-in-Hole Assembly
    2018 IEEE International Conference on Robotics and Biomimetics (ROBIO), 2018
    Co-Authors: Yuchen Wang, Zhao Xiong, Xusong Quan, Xiaodong Yuan, Peng Wang, Changchun Liu, Gaoming Hao, Zhou Hai
    Abstract:

    Large length-diameter ratio Peg-in-Hole assembly is a hard and significant issue in modern industry. The prediction and control of the contact force/torque play a crucial part in flexible assembly. They ensure that the contact force/torque data are within limits in assembly process, which can prevent jam and protect devices. In this paper, we propose a novel contact force/torque prediction and analysis model to solve the large length-diameter ratio Peg-in-Hole assembly problem in which the contact states are difficult to be obtained. Firstly, we establish a new force/torque prediction model with measured data to obtain the precision actual contact force/torque which is critical for assembly control. Then, a new contact analysis model for large length-diameter ratio Peg-in-Hole assembly is built to estimate the assembly contact states. At last, based on the proposed contact force/torque prediction and analysis model, we design a robot pose adjustment strategy for large length-diameter ratio Peg-in-Hole assembly. Experiment results demonstrate that the proposed model can meet the demands of large length-diameter ratio Peg-in-Hole assembly. The predicted error rates of force/torque are lower than 1 % and the mean force/torque in assembly process are lower than 5 N / 0.5 N.m by our model.

Ji Hun Bae - One of the best experts on this subject based on the ideXlab platform.

  • Compliance-Based Robotic Peg-in-Hole Assembly Strategy Without Force Feedback
    IEEE Transactions on Industrial Electronics, 2017
    Co-Authors: Hyeonjun Park, Dong Hyuk Lee, Jae-han Park, Moon-hong Baeg, Jaeheung Park, Ji Hun Bae
    Abstract:

    The Peg-in-Hole assembly is a representative robotic task that involves physical contact with the external environment. In this paper, in contrast to past research in the area, which has involved the utilization of such expensive devices as force/torque sensors or remote compliance mechanisms, an inexpensive method is proposed for Peg-in-Hole assembly without force feedback or passive compliance mechanisms. The method consists of an analysis of the state of contact between the peg and the hole as well as a strategy to overcome the inevitable positional uncertainty of the hole incurred in the recognition process. A control scheme was developed to yield compliant behavior from the robot with physical contact under the condition of hybrid position/force control. The effectiveness of the proposed method was experimentally verified using a robot manipulator with 8-degrees of freedom and a Peg-in-Hole apparatus with a small clearance (0.1 mm).

  • URAI - Dual arm Peg-in-Hole assembly with a programmed compliant system
    2014 11th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI), 2014
    Co-Authors: Hyeonjun Park, Ji Hun Bae, Jae-han Park, Moon-hong Baeg, Peter Ki Kim, Jaeheung Park
    Abstract:

    In order to accomplish a Peg-in-Hole task with a manipulator, a cognition process is needed to extract the positional information of the objects. However, in the case of a Peg-in-Hole task with an extremely small clearance, or for work in an unstructured environment, the cognition process has limited accuracy, caused by factors such as resolution and disturbance. Compliance has been considered as a solution to extremely small clearance in the Peg-in-Hole task. In order to give a manipulator the characteristic of compliance, an RCC (remote center compliance) device is generally used. This paper proposes an alternative: Programmed variable compliance, using virtual spring controllers in task space, and verifies its effectiveness by an experiment involving fine Peg-in-Hole insertion with a dual arm robot.

  • ISR - Intuitive Peg-in-Hole assembly strategy with a compliant manipulator
    IEEE ISR 2013, 2013
    Co-Authors: Hyeonjun Park, Ji Hun Bae, Jae-han Park, Moon-hong Baeg, Jaeheung Park
    Abstract:

    To realize a Peg-in-Hole assembly with a multi-degree of freedom (DOF) manipulator, the precise position of the hole is required. If the hole is not circular, orientation information is also necessary. A force/torque (F/T) sensor is widely used to sense the position and orientation of the hole. Attaching the F/T sensor on the wrist of a manipulator helps in estimating the position between the peg and hole. However, a person does not need precise information of an object when completing an assembly task. For example, when inserting a plug into an outlet, a person does not need to know the exact information and coordination about the position and orientation of the plug and outlet. A closer look at the process shows that the person tries to place a plug near the outlet and then finds the two holes by rubbing the plug against the outlet without looking. This paper introduces an intuitive assembly strategy inspired by this human behavior. This strategy does not need the precise location of the hole. Instead of an F/T sensor, this strategy adopts hybrid force/position control and passive compliance control for successful Peg-in-Hole assembly. The feasibility of the proposed strategy was verified through simulation and a hardware experiment.

Alin Albu-schaffer - One of the best experts on this subject based on the ideXlab platform.

  • ICRA - Robust, Locally Guided Peg-in-Hole using Impedance-Controlled Robots
    2020 IEEE International Conference on Robotics and Automation (ICRA), 2020
    Co-Authors: Korbinian Nottensteiner, Freek Stulp, Alin Albu-schaffer
    Abstract:

    We present an approach for the autonomous, robust execution of Peg-in-Hole assembly tasks. We build on a sampling-based state estimation framework, in which samples are weighted according to their consistency with the position and joint torque measurements. The key idea is to reuse these samples in a motion generation step, where they are assigned a second task-specific weight. The algorithm thereby guides the peg towards the goal along the configuration space. An advantage of the approach is that the user only needs to provide: the geometry of the objects as mesh data, as well as a rough estimate of the object poses in the workspace, and a desired goal state. Another advantage is that the local, online nature of our algorithm leads to robust behavior under uncertainty. The approach is validated in the case of our robotic setup and under varying uncertainties for the classical Peg-in-Hole problem subject to two different geometries.

Ken Chen - One of the best experts on this subject based on the ideXlab platform.

  • Screw Insertion Method in Peg-in-Hole Assembly for Axial Friction Reduction
    IEEE Access, 2019
    Co-Authors: Libin Song, Ken Chen, Jing Xu
    Abstract:

    Peg-in-Hole is one of the most frequent mating features between parts, where the large friction resistance and poor contact situations result in the failure of part mating. To address this problem, this paper proposes a screw insertion method in Peg-in-Hole assembly for axial friction reduction. First, the effect of screw motion on axial friction reduction is analyzed with point contact and face contact. Second, the screw insertion method in clearance-fit Peg-in-Hole assembly with point contact is discussed; this method works better than the conventional linear insertion method for jamming prevention; the reciprocate screw insertion strategy is also investigated to reduce the influence of axis offset on screw insertion. Third, the screw insertion method in interference-fit Peg-in-Hole assembly with face contact is discussed. Finally, axial friction reduction is validated with experiments of point contact with screw motion and experiments of screw insertion in clearance-fit and interference-fit Peg-in-Hole assembly.

  • ROBIO - Knowledge-Driven Deep Deterministic Policy Gradient for Robotic Multiple Peg-in-Hole Assembly Tasks
    2018 IEEE International Conference on Robotics and Biomimetics (ROBIO), 2018
    Co-Authors: Zhimin Hou, Kuangen Zhang, Dong Haiming, Quan Gao, Ken Chen
    Abstract:

    It remains a formidable challenge for traditional control strategies to perform automatic multiple Peg-in-Hole assembly tasks due to the complicated and dynamic contact states. Inspired by that human could generalize the learned skills to perform the different assembly tasks well, a general learning-based algorithm based on deep deterministic policy gradient (DDPG) is proposed. To make robots learn the multiple Peg-in-Hole assembly skills from experience efficiently and stably, the learning process is driven by the basic knowledge like PD force control strategy. To achieve a fast learning process in the real-world assembly tasks, a hybrid exploration strategy is applied to drive a efficient exploration during policy search phase. A dual Peg-in-Hole assembly simulation and real-world experiments are implemented to verify the effectiveness of the proposed algorithm. The performance measured by the assembly time and the maximum contact forces demonstrates that the multiple Peg-in-Hole assembly skills could be improved only after 150 training episodes in dual Peg-in-Hole assembly task.

  • Force control for a rigid dual Peg-in-Hole assembly
    Assembly Automation, 2017
    Co-Authors: Kuangen Zhang, Minhui Shi, Feng Liu, Ken Chen
    Abstract:

    Purpose This paper aims to realize the automatic assembly process for multiple rigid Peg-in-Hole components. Design/methodology/approach This paper develops fuzzy force control strategies for the rigid dual Peg-in-Hole assembly. Firstly the fuzzy force control strategies are presented. Secondly the contact states and contact forces are analyzed to prove the availability of the force control strategies. Findings The rigid dual Peg-in-Hole assembly experimental results show the effectiveness of the control strategies. Originality/value This paper proposes fuzzy force control strategies for a rigid dual Peg-in-Hole assembly task.

  • Laser tracker-based control for Peg-in-Hole assembly robot
    The 4th Annual IEEE International Conference on Cyber Technology in Automation Control and Intelligent, 2014
    Co-Authors: Jing Xu, Ken Chen
    Abstract:

    The Peg-in-Hole insertion is the most common and often one of the most important procedures in large-scale equipment manufacturing. However, in the process of Peg-in-Hole assembly operation using robot, the parts may not be assembled correctly or even be damaged because of the deviation causing by the inaccuracy of the assembly robot. To overcome this problem, this paper presents a kind of large-scale Peg-in-Hole robotic assembly system based on laser tracker and its corresponding control strategy. The simulation and analysis are also demonstrated to verify the system efficient.

Yanjiang Huang - One of the best experts on this subject based on the ideXlab platform.

  • Peg-in-Hole assembly based on master-slave coordination for a compliant dual-arm robot
    Assembly Automation, 2020
    Co-Authors: Yanjiang Huang, Jun Ota, Yanglong Zheng, Nian-feng Wang, Xianmin Zhang
    Abstract:

    The paper aims to propose an assembly scheme based on master–slave coordination for a compliant dual-arm robot to complete a Peg-in-Hole assembly task.,The proposed assembly scheme is inspired by the coordinated behaviors of human beings in the assembly process. The left arm and right arm of the robot are controlled to move alternately. The fixed arm and the moving arm are distinguished as the slave arm and the master arm, respectively. The position control model is used at the uncontacted stage, and the torque control model is used at the contacted stage.,The proposed assembly scheme is evaluated through Peg-in-Hole assembly experiments with different shapes of assembly piece. The round, triangle and square assembly piece with 0.5 mm maximum clearance between the peg and the hole can be assembled successfully based on the proposed method. Furthermore, three assembly strategies are investigated and compared in the Peg-in-Hole assembly experiments with different shapes of assembly piece.,The contribution of this study is that the authors propose an assembly scheme for a compliant dual-arm robot to overcome the low positioning accuracy and complete the Peg-in-Hole assembly tasks with different shapes parts.

  • Vision-guided Peg-in-Hole assembly by Baxter robot:
    Advances in Mechanical Engineering, 2017
    Co-Authors: Yanjiang Huang, Xianmin Zhang, Xunman Chen, Jun Ota
    Abstract:

    Dual-arm robot Baxter has been utilized in many applications. To use the Baxter robot realize a Peg-in-Hole assembly task, we proposed a step-by-step grasping strategy and a vision-guidance method for the Baxter robot. The step-by-step grasping strategy was used to position and grasp a peg and a hole on the working platform. At the assembling process, the positioning error was derived by the camera attached on the robot end-effector, and the positioning error was compensated through proportional–integral–derivative controller. Experiments were conducted to evaluate the grasping strategy and the vision-guidance method. Experimental results show that the Baxter robot can grasp the peg and the hole from the working platform, and the peg in hole with 1 mm clearance can be assembled successfully.

  • Peg-in-Hole Assembly Based on Two-phase Scheme and F/T Sensor for Dual-arm Robot
    Sensors (Basel Switzerland), 2017
    Co-Authors: Xianmin Zhang, Jun Ota, Yanglong Zheng, Yanjiang Huang
    Abstract:

    This paper focuses on Peg-in-Hole assembly based on a two-phase scheme and force/torque sensor (F/T sensor) for a compliant dual-arm robot, the Baxter robot. The coordinated operations of human beings in assembly applications are applied to the behaviors of the robot. A two-phase assembly scheme is proposed to overcome the inaccurate positioning of the compliant dual-arm robot. The position and orientation of assembly pieces are adjusted respectively in an active compliant manner according to the forces and torques derived by a six degrees-of-freedom (6-DOF) F/T sensor. Experiments are conducted to verify the effectiveness and efficiency of the proposed assembly scheme. The performances of the dual-arm robot are consistent with those of human beings in the Peg-in-Hole assembly process. The peg and hole with 0.5 mm clearance for round pieces and square pieces can be assembled successfully.

  • ROBIO - Peg-in-Hole assembly based on hybrid vision/force guidance and dual-arm coordination
    2017 IEEE International Conference on Robotics and Biomimetics (ROBIO), 2017
    Co-Authors: Yanglong Zheng, Xianmin Zhang, Yanlin Chen, Yanjiang Huang
    Abstract:

    In this paper, a Peg-in-Hole assembly strategy based on vision/force guidance and dual-arm coordination is proposed. Vision guidance using corner detection algorithm is applied for rough adjustment and ensures a suitable dual-arm operating space. To realize precise adjustment, position adjustment and orientation adjustment are realized respectively according to the forces and torques information detected by a 6-axis F/T sensor. Besides, master-slave arms are distinguished in dual-arm coordinated operation. The proposed strategy can be applied not only for round assembly parts, but also for triangle and square parts. Experimental results show that the proposed assembly strategy perform well for different-shaped parts and 0.5mm maximum clearance between peg and hole can be assembled successfully.