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

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 v...

Full description

Bibliographic Details
Main Authors: Hongtai Cheng, Wei Li
Format: Article
Language:English
Published: Hindawi Limited 2018-01-01
Series:Shock and Vibration
Online Access:http://dx.doi.org/10.1155/2018/2945314
id doaj-966dfcfd00fd4a7f82286e4c27a60ddd
record_format Article
spelling doaj-966dfcfd00fd4a7f82286e4c27a60ddd2020-11-24T21:21:43ZengHindawi LimitedShock and Vibration1070-96221875-92032018-01-01201810.1155/2018/29453142945314Reducing the Frame Vibration of Delta Robot in Pick and Place Application: An Acceleration Profile Optimization ApproachHongtai Cheng0Wei Li1Department of Mechanical Engineering and Automation, Northeastern University, Shenyang, Liaoning Province 110819, ChinaDepartment of Electrical Engineering, Dalian University of Technology, Dalian, Liaoning Province, ChinaDelta 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.http://dx.doi.org/10.1155/2018/2945314
collection DOAJ
language English
format Article
sources DOAJ
author Hongtai Cheng
Wei Li
spellingShingle Hongtai Cheng
Wei Li
Reducing the Frame Vibration of Delta Robot in Pick and Place Application: An Acceleration Profile Optimization Approach
Shock and Vibration
author_facet Hongtai Cheng
Wei Li
author_sort Hongtai Cheng
title Reducing the Frame Vibration of Delta Robot in Pick and Place Application: An Acceleration Profile Optimization Approach
title_short Reducing the Frame Vibration of Delta Robot in Pick and Place Application: An Acceleration Profile Optimization Approach
title_full Reducing the Frame Vibration of Delta Robot in Pick and Place Application: An Acceleration Profile Optimization Approach
title_fullStr Reducing the Frame Vibration of Delta Robot in Pick and Place Application: An Acceleration Profile Optimization Approach
title_full_unstemmed Reducing the Frame Vibration of Delta Robot in Pick and Place Application: An Acceleration Profile Optimization Approach
title_sort reducing the frame vibration of delta robot in pick and place application: an acceleration profile optimization approach
publisher Hindawi Limited
series Shock and Vibration
issn 1070-9622
1875-9203
publishDate 2018-01-01
description 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.
url http://dx.doi.org/10.1155/2018/2945314
work_keys_str_mv AT hongtaicheng reducingtheframevibrationofdeltarobotinpickandplaceapplicationanaccelerationprofileoptimizationapproach
AT weili reducingtheframevibrationofdeltarobotinpickandplaceapplicationanaccelerationprofileoptimizationapproach
_version_ 1725998640320741376