Dynamic error modeling and compensation in high speed delta robot pick-and-place process

Cheng, Hongtai; Zhang, Zhifei; Li, Wei

doi:10.1109/cyber.2015.7287906

Cited by 7 publications

(6 citation statements)

References 10 publications

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“…d For i=1,2,…,N, calculate the normalized weights w k i i Obtain each pixel value via (5) ii Calculate the weight of each particle via (17) iii Normalize the weight of each particle via (9) e Check whether λ> λ t , if so, update template with ( 19 pose of target is needed. In this paper, we employ a RGB-D camera to estimate the 3D pose of target.…”

Section: Grasp Execution With Position Based Visual Servoingmentioning

confidence: 99%

“…In recent years, researchers have also achieved many impressive research results in the field of moving objects tracking and grasping. Besides the most common scenarios of picking and placing goods on single-dimensional moving conveyor belts in industry [8][9][10], one of the most representative application is the catching of free flying object. Billard et al [11,12] carried out a series of fruitful studies on this issue, in which the free-flying objects's grasping configuration is learned by a programming-by-demonstration approach.…”

Section: Introductionmentioning

confidence: 99%

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Tracking and grasping of moving target based on accelerated geometric particle filter on colored image

Gong

Qiu

Tao

et al. 2020

Sci. China Technol. Sci.

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Visual tracking and grasping of moving object is a challenging task in the field of robotic manipulation, which also has great potential in applications such as human-robot collaboration. Based on the particle filtering framework and position-based visual servoing, this paper proposes a new method for visual tracking and grasping of randomly moving objects. A geometric particle filter tracker is established for visual tracking. In order to deal with the tracking efficiency issue for particle filter, edge detection and morphological dilation are employed to reduce the computation burden of geometric particle filtering. Meanwhile, the HSV image feature is employed instead of the grayscale feature to improve the tracking algorithm's robustness to illumination change. A grasping strategy combining tracking and interception is adopted along with the position-based visual servoing (PBVS) method to achieve stable grasp of the target. Comprehensive comparisons on open source dataset and a large number of experiments on real robot system are conducted, which demonstrate the proposed method has competitive performance in random moving object tracking and grasping.

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Section: Grasp Execution With Position Based Visual Servoingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Tracking and grasping of moving target based on accelerated geometric particle filter on colored image

Gong

Qiu

Tao

et al. 2020

Sci. China Technol. Sci.

View full text Add to dashboard Cite

show abstract

“…Results of aligning with Y-axis are similar. Pick and Place Motion (PPM) is a door shaped trajectory consisted of one horizontal, two vertical, and two smooth transition segments as shown in Figure 2 [25]. The trajectory formed by points P0→P3 in Figure 2 is a typical PPM, where P0 is the pick-up location and P3 is the put-down location.…”

Section: Delta Robot In Pick Andmentioning

confidence: 99%

Reducing the Frame Vibration of Delta Robot in Pick and Place Application: An Acceleration Profile Optimization Approach

Cheng

Wei

2018

Shock and Vibration

Self Cite

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Delta robot is typically mounted on a frame and performs high speed pick and place tasks from top to bottom. Because of its outstanding accelerating capability and higher center of mass, the Delta robot can generate significant frame vibration. Existing trajectory smoothing methods mainly focus on vibration reduction for the robot instead of the frame, and modifying the frame structure increases the manufacturing cost. In this paper, an acceleration profile optimization approach is proposed to reduce the Delta robot-frame vibration. The profile is determined by the maximum jerk, acceleration, and velocity. The pick and place motion (PPM) and resulting frame vibration are analyzed in frequency domain. Quantitative analysis shows that frame vibration can be reduced by altering those dynamic motion parameters. Because the analytic model is derived based on several simplifications, it cannot be directly applied. A surrogate model-based optimization method is proposed to solve the practical issues. By directly executing the PPM with different parameters and measuring the vibration, a model is derived using Gaussian Process Regression (GPR). In order to reduce the frame vibration without sacrificing robot efficiency, those two goals are fused together according to their priorities. Based on the surrogate model, a single objective optimization problem is formulated and solved by Genetic Algorithm (GA). Experimental results show effectiveness of the proposed method. Behavior of the optimal parameters also verifies the robot-frame vibration mechanism.

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“…Figure 1 shows a commonly used configuration. The workpieces are supplied through conveyors and the robot picks them from conveyor and places them on target locations (boxes, plates or other conveyors Cheng et al (2015a). Pick-and-place motion (PPM) is a door-shaped trajectory consisting of one horizontal, two vertical and two smooth transition segments (Su et al , 2018); Huang et al (2016).…”

Section: Introductionmentioning

confidence: 99%

Sensorless force estimation and control of Delta robot with limited access interface

Cheng

Jiang

2018

Self Cite

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Purpose Delta robot is a parallel robot specifically designed for high-speed pick and place tasks. However, sometimes they are asked to perform additional assembling and squeezing actions, which is beyond the capability of position-controlled Delta robots. Force sensors may be expensive and add mass to the system. Therefore, the purpose of this paper is to study sensorless force control of Delta robots using limited access interface. Design/methodology/approach Static force analysis is performed to establish a relation between joint torques and external forces. The joint torques are observed from signals provided by motor drivers. A distributed mass model is proposed to compensate the gravity of upper arms and forearms. To minimize the effect of backlash and nonlinear frictions brought by gearboxes, model parameters are calibrated in two separated modes: “LIFTING” and “LOWERING”. Finally, a hybrid force estimation model is built to deal with both cases simultaneously. Surrogate model-based force control law is proposed to increase the force control loop rate and handle the force control problem for discrete position-controlled Delta robots. Findings The results show that the force estimation model is effective and mode separation can significantly improve the accuracy. The force control laws indeed stabilize the robot in desired states. Originality/value The proposed solution is based on position-controlled commercial Delta robot and requires no additional force sensor. It is able to extend Delta robots’ capability and meet requirements of emerging complex tasks.

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Dynamic error modeling and compensation in high speed delta robot pick-and-place process

Cited by 7 publications

References 10 publications

Tracking and grasping of moving target based on accelerated geometric particle filter on colored image

Tracking and grasping of moving target based on accelerated geometric particle filter on colored image

Reducing the Frame Vibration of Delta Robot in Pick and Place Application: An Acceleration Profile Optimization Approach

Sensorless force estimation and control of Delta robot with limited access interface

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