Simultaneous path placement and trajectory planning optimization for a redundant coordinated robotic workcell

FarzanehKaloorazi, MohammadHadi; Bonev, Ilian A.; Birglen, Lionel

doi:10.1016/j.mechmachtheory.2018.08.022

Cited by 21 publications

(7 citation statements)

References 33 publications

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“…Wang et al studied the application of the particle swarm optimization (PSO) strategy in the coordinated trajectory planning of dual-arm space robots in free-floating mode, and realized the coordinated control of the dual-arm space robot system [14]. Farzaneh Kaloorazi proposed a method for optimizing the trajectory planning and layout of a given path in a redundant coordinated robot working unit using PSO, and achieved good experimental results [15]. Xie Y et al proposed a trajectory planning algorithm that can minimize the disturbance of a spacecraft to a spacecraft base for a dual robotic space robot [16].…”

Section: Introductionmentioning

confidence: 99%

Autonomous Operation Method of Multi-DOF Robotic Arm Based on Binocular Vision

Fan

Lin

et al. 2019

Applied Sciences

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Robotic arms with autonomous operation capabilities are currently widely used in real life, such as fruit picking, cargo handling, and workpiece assembly. However, the common autonomous operation methods of the robotic arm have some disadvantages, such as poor universality, low robustness, and difficult implementation. An autonomous operation method of multi-DOF (Multiple Degree of Freedom) robotic arm is proposed in this study on the basis of binocular vision. First, a target object extraction method based on extracting target feature points is proposed, and combined with the binocular positioning principle to obtain the spatial position of the target object. Second, in order to improve the working efficiency of the robotic arm, the robotic arm motion trajectory is planned on the basis of genetic algorithm in the joint space. Finally, a small physical prototype model is built for experimental verification. The experimental results show that the relative positioning error of the target object can reach 1.19% in the depth of field of 70–200 mm. The average grab error, variance, and grab success rate of the robot arm are 14 mm, 6.5 mm, and 83%, respectively. This shows that the method proposed in this paper has the advantages of high robustness, good versatility and easy implementation.

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Section: Introductionmentioning

confidence: 99%

Autonomous Operation Method of Multi-DOF Robotic Arm Based on Binocular Vision

Fan

Lin

et al. 2019

Applied Sciences

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“…The sensor is attached to the end-effector and it is not easy to install for some applications. FarzanehKaloorazi et al [14] optimized the trajectory planning of a robotic work cell by using particle swarm optimization (PSO). However, the PSO algorithm needs complex computation and can cause a delay in realtime execution.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Hybrid Filter for Vision‐Based Pose Estimation of a Hexa Parallel Robot

Huynh

Kuo

2021

Journal of Sensors

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One of the problems with industrial robots is their ability to accurately locate the pose of the end-effector. Over the years, many other solutions have been studied including static calibration and dynamic positioning. This paper presents a novel approach for pose estimation of a Hexa parallel robot. The vision system uses three simple color feature points fixed on the surface of the end-effector to measure the pose of the robot. The Intel RealSense Camera D435i is used as a 3D measurement of feature points, which offers a cheap solution and high accuracy in positioning. Based on the constraint of three color feature points, the pose of the end-effector, including position and orientation, is determined. A dynamic hybrid filter is designed to correct the vision-based pose measurement. The complementary filter is used to eliminate the noise of image processing due to environmental light source interference. The unscented Kalman filter is designed to smooth out the pose estimation of the vision system based on robot’s kinematic parameters. The combination of two filters in the same control scheme contributes to increased stability and improved accuracy of robot’s positioning. The simulation, experiment, and comparison demonstrate the effectiveness and feasibility of the proposed method.

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“…To highlight the advantages of robotic deburring, an optimization of the deburring toolpath with respect to the robot stiffness is required. This is essentially a well-known optimization problem for workpiece or trajectory placement [21][22][23], where robot stiffness is used as the optimization objective [24][25][26][27][28].…”

Section: Introductionmentioning

confidence: 99%

Stiffness-Based Cell Setup Optimization for Robotic Deburring with a Rotary Table

2021

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Deburring is recognized as an ideal technology for robotic automation. However, since the low stiffness of the robot can affect the deburring quality and the performance of an industrial robot is generally inhomogeneous over its workspace, a cell setup must be found that allows the robot to track the toolpath with the desired performance. In this work, the problems of robotic deburring are addressed by integrating components commonly used in the machining industry. A rotary table is integrated with the robotic deburring cell to increase the effective reach of the robot and enable it to machine a large workpiece. A genetic algorithm (GA) is used to optimize the placement of the workpiece based on the stiffness of the robot, and a local minimizer is used to maximize the stiffness of the robot along the deburring toolpath. During cutting motions, small table rotations are allowed so that the robot maintains high stiffness, and during non-cutting motions, large table rotations are allowed to reposition the workpiece. The stiffness of the robot is modeled by an artificial neural network (ANN). The results confirm the need to optimize the cell setup, since many optimizers cannot track the toolpath, while for the successful optimizers, a performance imbalance occurs along the toolpath.

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Simultaneous path placement and trajectory planning optimization for a redundant coordinated robotic workcell

Cited by 21 publications

References 33 publications

Autonomous Operation Method of Multi-DOF Robotic Arm Based on Binocular Vision

Autonomous Operation Method of Multi-DOF Robotic Arm Based on Binocular Vision

Dynamic Hybrid Filter for Vision‐Based Pose Estimation of a Hexa Parallel Robot

Stiffness-Based Cell Setup Optimization for Robotic Deburring with a Rotary Table

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