Trajectory Planning for Reconfigurable Industrial Robots Designed to Operate in a High Precision Manufacturing Industry

被引:9
|
作者
Avram, Oliver [1 ]
Valente, Anna [1 ]
机构
[1] ISTePS Inst Syst & Technol Sustainable Prod, SUPSI, Galleria 2, CH-6928 Manno, Switzerland
关键词
Robot reconfiguration; Motion planning; Jerk-bounded trajectory; MANIPULATORS; ALGORITHMS;
D O I
10.1016/j.procir.2016.11.080
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
This paper presents an algorithm for an automated planning of time-jerk optimal trajectories on a reconfigurable robot with an anthropomorphic structure. The trajectory planning algorithm is designed to provide reachable input set-points for the reconfigurable control system to accommodate not only changes in task objectives but also various reconfigurations of the robot kinematic structure and motion behavior adaptation in response to operational constraints. Firstly, appropriate reference frames are defined on the robotic modules and the position and orientation of the end effector in the Cartesian space is dynamically generated through a reconfigurable forward kinematics module. Secondly, through an iterative inverse kinematic method, the robot configuration space for the start and goal destinations and the geometric path for every motion tasks are generated. Finally, the joint space trajectories with coordinated motion profiles are generated by incorporating the motion laws and joint kinematic parameter values. The general outcome of the algorithm is a trajectory plan of the robot joints expressed as a time history of the robot motion. The trajectories aredynamically generated to satisfy widely varying tasks, constraints and objectives aiming towards a fully reconfigurable control without any hardware or software adjustment. (C) 2016 The Authors. Published by Elsevier B.V.
引用
收藏
页码:461 / 466
页数:6
相关论文
共 50 条
  • [41] Trajectory Planning with Minimum Synthesis Error for Industrial Robots Using Screw Theory
    Zhifeng Liu
    Jingjing Xu
    Qiang Cheng
    Yongsheng Zhao
    Yanhu Pei
    Congbin Yang
    [J]. International Journal of Precision Engineering and Manufacturing, 2018, 19 : 183 - 193
  • [42] Review of performance testing of high precision reducers for industrial robots
    Qiu, Zurong
    Xue, Jie
    [J]. MEASUREMENT, 2021, 183
  • [43] Theoretical and Kinematic Solution of High Reconfigurable Grasping for Industrial Manufacturing
    Canali, Carlo
    Rahman, Nahian
    Chen, Fei
    D'imperio, Mariapaola
    Caldwell, Darwin
    Cannella, Ferdinando
    [J]. 27TH INTERNATIONAL CONFERENCE ON FLEXIBLE AUTOMATION AND INTELLIGENT MANUFACTURING, FAIM2017, 2017, 11 : 265 - 274
  • [44] Region-adaptive path planning for precision optical polishing with industrial robots
    Wan, Songlin
    Zhang, Xiangchao
    Xu, Min
    Wang, Wei
    Jiang, Xiangqian
    [J]. OPTICS EXPRESS, 2018, 26 (18): : 23782 - 23795
  • [45] Theoretical and Kinematic Solution of High Reconfigurable Grasping for Industrial Manufacturing
    Chen, Fei
    Cannella, Ferdinando
    Canali, Carlo
    Eytan, Amit
    Bottero, Aldo
    Caldwell, Darwin
    [J]. 2013 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND BIOMIMETICS (ROBIO), 2013, : 734 - 739
  • [46] High precision trajectory planning on freeform surfaces for robotic manipulators
    Freitas, Renan S.
    Soares, Eduardo E. M.
    Costa, Ramon R.
    Carvalho, Breno B.
    [J]. 2017 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS), 2017, : 3695 - 3700
  • [47] High-Precision Mobile Robotic Manipulator for Reconfigurable Manufacturing Systems
    Inoue, Shinichi
    Urata, Akihisa
    Kodama, Takumi
    Huwer, Tobias
    Maruyama, Yuya
    Fujita, Sho
    Shinno, Hidenori
    Yoshioka, Hayato
    [J]. INTERNATIONAL JOURNAL OF AUTOMATION TECHNOLOGY, 2021, 15 (05) : 651 - 660
  • [48] Industry 4.0 and Industrial Robots: A Study from the Perspective of Manufacturing Company Employees
    Cigdem, Semsettin
    Meidute-Kavaliauskiene, Ieva
    Yildiz, Bulent
    [J]. LOGISTICS-BASEL, 2023, 7 (01):
  • [49] Effects of genetic algorithm parameters on trajectory planning for 6-DOF industrial robots
    Cakir, Mustafa
    Butun, Erhan
    Kayman, Yekta
    [J]. INDUSTRIAL ROBOT-THE INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH AND APPLICATION, 2006, 33 (03): : 205 - 215
  • [50] Statistical evaluation of an evolutionary algorithm for minimum time trajectory planning problem for industrial robots
    Abu-Dakka, Fares J.
    Assad, Iyad F.
    Alkhdour, Rasha M.
    Abderahim, Mohamed
    [J]. INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2017, 89 (1-4): : 389 - 406