Optimizing Kinematic Modeling and Self-Collision Detection of a Mobile Manipulator Robot by Considering the Actual Physical Structure
In this paper, an optimized kinematic modeling method to accurately describe the actual structure of a mobile manipulator robot with a manipulator similar to the universal robot (UR5) is developed, and an improved self-collision detection technology realized for improving the description accuracy of...
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Published in | Applied sciences Vol. 11; no. 22; p. 10591 |
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Main Authors | , , , , |
Format | Journal Article |
Language | English |
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01.11.2021
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ISSN | 2076-3417 2076-3417 |
DOI | 10.3390/app112210591 |
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Abstract | In this paper, an optimized kinematic modeling method to accurately describe the actual structure of a mobile manipulator robot with a manipulator similar to the universal robot (UR5) is developed, and an improved self-collision detection technology realized for improving the description accuracy of each component and reducing the time required for approximating the whole robot is introduced. As the primary foundation for trajectory tracking and automatic navigation, the kinematic modeling technology of the mobile manipulator has been the subject of much interest and research for many years. However, the kinematic model established by various methods is different from the actual physical model due to the fact that researchers have mainly focused on the relationship between driving joints and the end positions while ignoring the physical structure. To improve the accuracy of the kinematic model, we present a kinematic modeling method with the addition of key points and coordinate systems to some components that failed to model the physical structure based on the classical method. Moreover, self-collision detection is also a primary problem for successfully completing the specified task of the mobile manipulator. In traditional self-collision detection technology, the description of each approximation is determined by the spatial transformation of each corresponding component in the mobile manipulator robot. Unlike the traditional technology, each approximation in the paper is directly established by the physical structure used in the kinematic modeling method, which significantly reduces the complicated analysis and shortens the required time. The numerical simulations prove that the kinematic model with the addition of key point technology is similar to the actual structure of mobile manipulator robots, and the self-collision detection technology proposed in the article effectively improves the performance of self-collision detection. Additionally, the experimental results prove that the kinematic modeling method and self-collision detection technology outlined in this paper can optimize the inverse kinematics solution. |
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AbstractList | In this paper, an optimized kinematic modeling method to accurately describe the actual structure of a mobile manipulator robot with a manipulator similar to the universal robot (UR5) is developed, and an improved self-collision detection technology realized for improving the description accuracy of each component and reducing the time required for approximating the whole robot is introduced. As the primary foundation for trajectory tracking and automatic navigation, the kinematic modeling technology of the mobile manipulator has been the subject of much interest and research for many years. However, the kinematic model established by various methods is different from the actual physical model due to the fact that researchers have mainly focused on the relationship between driving joints and the end positions while ignoring the physical structure. To improve the accuracy of the kinematic model, we present a kinematic modeling method with the addition of key points and coordinate systems to some components that failed to model the physical structure based on the classical method. Moreover, self-collision detection is also a primary problem for successfully completing the specified task of the mobile manipulator. In traditional self-collision detection technology, the description of each approximation is determined by the spatial transformation of each corresponding component in the mobile manipulator robot. Unlike the traditional technology, each approximation in the paper is directly established by the physical structure used in the kinematic modeling method, which significantly reduces the complicated analysis and shortens the required time. The numerical simulations prove that the kinematic model with the addition of key point technology is similar to the actual structure of mobile manipulator robots, and the self-collision detection technology proposed in the article effectively improves the performance of self-collision detection. Additionally, the experimental results prove that the kinematic modeling method and self-collision detection technology outlined in this paper can optimize the inverse kinematics solution. |
Author | Li, Minghao Jiang, Jianfeng Luo, Qingsheng Qiao, Lijun Luo, Xiao |
Author_xml | – sequence: 1 givenname: Lijun orcidid: 0000-0002-2667-1713 surname: Qiao fullname: Qiao, Lijun – sequence: 2 givenname: Xiao orcidid: 0000-0003-2574-4594 surname: Luo fullname: Luo, Xiao – sequence: 3 givenname: Qingsheng orcidid: 0000-0002-5549-8016 surname: Luo fullname: Luo, Qingsheng – sequence: 4 givenname: Minghao orcidid: 0000-0002-5648-8776 surname: Li fullname: Li, Minghao – sequence: 5 givenname: Jianfeng orcidid: 0000-0001-9600-8063 surname: Jiang fullname: Jiang, Jianfeng |
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Cites_doi | 10.3389/fnbot.2017.00053 10.3901/CJME.2013.03.585 10.1016/j.matcom.2019.11.002 10.1007/s11071-013-0776-0 10.1017/S0263574700003295 10.1177/1729881416666782 10.1016/j.isatra.2018.07.023 10.1109/TII.2018.2879426 10.1016/j.neucom.2018.01.002 10.1016/j.cad.2009.04.010 10.1007/s10846-017-0705-4 10.3390/app10175893 10.14429/dsj.70.14119 10.1016/j.jfranklin.2019.09.045 10.1109/ROBOT.2010.5509554 10.1007/s41315-019-00090-7 10.3390/s20247249 10.1016/j.robot.2019.07.013 10.1016/j.mechmachtheory.2020.103919 10.1109/TIE.2017.2674624 10.1007/s10846-017-0713-4 10.1016/j.ast.2020.105882 10.1016/j.robot.2020.103554 10.1109/ICRA.2013.6630836 10.1155/2019/6857106 10.3390/s21030890 10.1109/TMECH.2006.871092 10.1007/s10846-017-0686-3 10.1007/s10846-008-9205-x 10.1002/rob.20096 10.1016/j.robot.2019.103344 10.1016/j.rcim.2017.05.013 10.1016/j.biosystemseng.2010.01.007 10.1109/ACCESS.2019.2925428 |
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References | Li (ref_17) 2019; 7 Liao (ref_36) 2019; 3 Henten (ref_34) 2010; 106 Ju (ref_31) 2001; 19 Jin (ref_6) 2018; 85 My (ref_20) 2020; 170 Wang (ref_21) 2019; 2019 ref_33 ref_10 Seo (ref_4) 2018; 80 Qiu (ref_24) 2008; 52 Savino (ref_25) 2020; 357 Chang (ref_28) 2010; 42 ref_39 Wu (ref_3) 2017; 11 Tang (ref_23) 2006; 11 ref_38 ref_37 Bostelman (ref_9) 2018; 92 Mishra (ref_15) 2020; 70 Jin (ref_13) 2017; 64 Baron (ref_41) 2020; 12 Park (ref_8) 2020; 103 Wang (ref_18) 2016; 13 Duguleana (ref_35) 2012; 28 Patel (ref_32) 2005; 22 Safeea (ref_7) 2019; 119 Tawfik (ref_19) 2019; 26 Alanis (ref_43) 2018; 15 Han (ref_30) 2018; 49 Du (ref_11) 2013; 26 Chen (ref_14) 2019; 15 ref_40 ref_1 Gong (ref_5) 2020; 152 Adorno (ref_26) 2018; 91 Silva (ref_27) 2018; 91 Mashali (ref_12) 2016; 2016 Zhang (ref_42) 2020; 129 Tao (ref_22) 2020; 10 Park (ref_2) 2020; 124 Zhong (ref_16) 2013; 73 Xiaodong (ref_29) 2015; 9 |
References_xml | – volume: 11 start-page: 53 year: 2017 ident: ref_3 article-title: A developmental learning approach of mobile manipulator via playing publication-title: Front. Neurorobot. doi: 10.3389/fnbot.2017.00053 – volume: 26 start-page: 585 year: 2013 ident: ref_11 article-title: Dexterity analysis for omni-directional wheeled mobile manipulator based on double quaternion publication-title: Chin. J. Mech. Eng. doi: 10.3901/CJME.2013.03.585 – volume: 170 start-page: 300 year: 2020 ident: ref_20 article-title: Modeling and computation of real-time applied torques and non-holonomic constraint forces/moment, and optimal design of wheels for an autonomous security robot tracking a moving target publication-title: Math. Comput. Simul. doi: 10.1016/j.matcom.2019.11.002 – volume: 73 start-page: 167 year: 2013 ident: ref_16 article-title: System modeling and tracking control of mobile manipulator subjected to dynamic interaction and uncertainty publication-title: Nonlinear Dyn. doi: 10.1007/s11071-013-0776-0 – volume: 19 start-page: 381 year: 2001 ident: ref_31 article-title: Fast and accurate collision detection based on enclosed ellipsoid publication-title: Robotica doi: 10.1017/S0263574700003295 – volume: 12 start-page: 1 year: 2020 ident: ref_41 article-title: Measurement of unidirectional pose accuracy and repeatability of the collaborative robot UR5 publication-title: Adv. Mech. Eng. – volume: 13 start-page: 1 year: 2016 ident: ref_18 article-title: Comparative study on the redundancy of mobile single- and dual-arm robots publication-title: Int. J. Adv. Robot. Syst. doi: 10.1177/1729881416666782 – volume: 10 start-page: 1 year: 2020 ident: ref_22 article-title: Kinematic modeling and control of mobile robot for large-scale workpiece machining publication-title: Proc. Inst. Mech. Eng. Part B J. Eng. Manuf. – ident: ref_39 – ident: ref_40 – volume: 80 start-page: 322 year: 2018 ident: ref_4 article-title: Dual closed-loop sliding mode control for a decoupled three-link wheeled mobile manipulator publication-title: ISA Trans. doi: 10.1016/j.isatra.2018.07.023 – volume: 15 start-page: 1202 year: 2019 ident: ref_14 article-title: Dexterous Grasping by Manipulability Selection for Mobile Manipulator with Visual Guidance publication-title: IEEE Trans. Ind. Inform. doi: 10.1109/TII.2018.2879426 – volume: 85 start-page: 23 year: 2018 ident: ref_6 article-title: Robot manipulator control using neural networks: A survey publication-title: Neurocomputing doi: 10.1016/j.neucom.2018.01.002 – volume: 26 start-page: 55 year: 2019 ident: ref_19 article-title: Motion Control of Non-Holonomic Wheeled Mobile Robot Based on Particle Swarm Optimization Method (PSO) publication-title: Assoc. Arab Univ. J. Eng. Sci. – volume: 42 start-page: 50 year: 2010 ident: ref_28 article-title: Efficient collision detection using a dual OBB-sphere bounding volume hierarchy publication-title: CAD Comput. Aided Des. doi: 10.1016/j.cad.2009.04.010 – volume: 92 start-page: 65 year: 2018 ident: ref_9 article-title: Model of Mobile Manipulator Performance Measurement using SysML publication-title: J. Intell. Robot. Syst. Theory Appl. doi: 10.1007/s10846-017-0705-4 – volume: 9 start-page: 849 year: 2015 ident: ref_29 article-title: Real-time Detection of Space Manipulator publication-title: World Acad. Sci. Eng. Technol. – ident: ref_37 doi: 10.3390/app10175893 – volume: 70 start-page: 72 year: 2020 ident: ref_15 article-title: Simplified motion control of a vehicle-manipulator for the coordinated mobile manipulation publication-title: Def. Sci. J. doi: 10.14429/dsj.70.14119 – volume: 357 start-page: 142 year: 2020 ident: ref_25 article-title: Pose consensus based on dual quaternion algebra with application to decentralized formation control of mobile manipulators publication-title: J. Franklin Inst. doi: 10.1016/j.jfranklin.2019.09.045 – ident: ref_10 doi: 10.1109/ROBOT.2010.5509554 – volume: 2016 start-page: 1 year: 2016 ident: ref_12 article-title: Mobile manipulator dual-trajectory tracking using control variables introduced to end-effector task vector publication-title: World Autom. Congr. Proc. – volume: 3 start-page: 115 year: 2019 ident: ref_36 article-title: Optimization-based motion planning of mobile manipulator with high degree of kinematic redundancy publication-title: Int. J. Intell. Robot. Appl. doi: 10.1007/s41315-019-00090-7 – ident: ref_1 doi: 10.3390/s20247249 – volume: 119 start-page: 278 year: 2019 ident: ref_7 article-title: On-line collision avoidance for collaborative robot manipulators by adjusting off-line generated paths: An industrial use case publication-title: Rob. Auton. Syst. doi: 10.1016/j.robot.2019.07.013 – volume: 152 start-page: 103919 year: 2020 ident: ref_5 article-title: Obstacle-crossing Strategy and Formation Parameters Optimization of a Multi-tracked-mobile-robot System with a Parallel Manipulator publication-title: Mech. Mach. Theory doi: 10.1016/j.mechmachtheory.2020.103919 – volume: 64 start-page: 4710 year: 2017 ident: ref_13 article-title: Manipulability Optimization of Redundant Manipulators Using Dynamic Neural Networks publication-title: IEEE Trans. Ind. Electron. doi: 10.1109/TIE.2017.2674624 – volume: 91 start-page: 263 year: 2018 ident: ref_26 article-title: Whole-Body Kinematic Control of Nonholonomic Mobile Manipulators Using Linear Programming publication-title: J. Intell. Robot. Syst. Theory Appl. doi: 10.1007/s10846-017-0713-4 – volume: 103 start-page: 105882 year: 2020 ident: ref_8 article-title: Stereo vision based obstacle collision avoidance for a quadrotor using ellipsoidal bounding box and hierarchical clustering publication-title: Aerosp. Sci. Technol. doi: 10.1016/j.ast.2020.105882 – volume: 129 start-page: 103554 year: 2020 ident: ref_42 article-title: A novel coordinated motion planner based on capability map for autonomous mobile manipulator publication-title: Robot. Auton. Syst. doi: 10.1016/j.robot.2020.103554 – ident: ref_33 doi: 10.1109/ICRA.2013.6630836 – volume: 2019 start-page: 6857106 year: 2019 ident: ref_21 article-title: Kinematical research of free-floating space-robot system at position level based on screw theory publication-title: Int. J. Aerosp. Eng. doi: 10.1155/2019/6857106 – ident: ref_38 doi: 10.3390/s21030890 – volume: 11 start-page: 169 year: 2006 ident: ref_23 article-title: Screw-theoretic analysis framework for cooperative payload transport by mobile manipulator collectives publication-title: IEEE/ASME Trans. Mechatron. doi: 10.1109/TMECH.2006.871092 – volume: 91 start-page: 249 year: 2018 ident: ref_27 article-title: Whole-body Control of a Mobile Manipulator Using Feedback Linearization and Dual Quaternion Algebra publication-title: J. Intell. Robot. Syst. Theory Appl. doi: 10.1007/s10846-017-0686-3 – volume: 52 start-page: 101 year: 2008 ident: ref_24 article-title: Modeling and analysis of the dynamics of an omni-directional mobile manipulators system publication-title: J. Intell. Robot. Syst. Theory Appl. doi: 10.1007/s10846-008-9205-x – volume: 22 start-page: 737 year: 2005 ident: ref_32 article-title: A collision-avoidance scheme for redundant manipulators: Theory and experiments publication-title: J. Robot. Syst. doi: 10.1002/rob.20096 – volume: 124 start-page: 103344 year: 2020 ident: ref_2 article-title: Active robot-assisted feeding with a general-purpose mobile manipulator: Design, evaluation, and lessons learned publication-title: Rob. Auton. Syst. doi: 10.1016/j.robot.2019.103344 – volume: 49 start-page: 98 year: 2018 ident: ref_30 article-title: Dynamic obstacle avoidance for manipulators using distance calculation and discrete detection publication-title: Robot. Comput. Integr. Manuf. doi: 10.1016/j.rcim.2017.05.013 – volume: 106 start-page: 112 year: 2010 ident: ref_34 article-title: Collision-free inverse kinematics of the redundant seven-link manipulator used in a cucumber picking robot publication-title: Biosyst. Eng. doi: 10.1016/j.biosystemseng.2010.01.007 – volume: 28 start-page: 132 year: 2012 ident: ref_35 article-title: Obstacle avoidance of redundant manipulators using neural networks based reinforcement learning publication-title: Robot. Comput. Integr. Manuf. – volume: 15 start-page: 1 year: 2018 ident: ref_43 article-title: Inverse kinematics of mobile manipulators based on differential evolution publication-title: Int. J. Adv. Robot. Syst. – volume: 7 start-page: 88301 year: 2019 ident: ref_17 article-title: Dynamical Obstacle Avoidance of Task- Constrained Mobile Manipulation Using Model Predictive Control publication-title: IEEE Access doi: 10.1109/ACCESS.2019.2925428 |
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SubjectTerms | actual physical structure Approximation kinematic modeling Kinematics Mathematical models Methods mobile manipulator robot Researchers Robots self-collision detection |
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Title | Optimizing Kinematic Modeling and Self-Collision Detection of a Mobile Manipulator Robot by Considering the Actual Physical Structure |
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