Trajectory Planning and Optimization for a Par4 Parallel Robot Based on Energy Consumption
Source abstract
Abstract
A study on trajectory planning and optimization for a Par4 parallel robot was carried out, based on energy consumption in high-speed picking and placing. In the end-effector operating space of the Par4 parallel robot, the rectangular transition of the pick-and-place trajectory was rounded by a Lamé curve. A piecewise design method was adopted to accomplish trajectory shape planning for displacement, velocity and acceleration. To make the Par4 robot’s end run more smoothly and to reduce residual vibration, asymmetric fifth-order and sixth-order polynomial motion laws were employed. With the aim of reaching the minimum mechanical energy consumption for the Par4 parallel robot, the recently proposed Grey Wolf Optimizer (GWO) algorithm was adopted to optimize the planning trajectory. The validity of the design method was verified by experiments, and it was found that the minimum mechanical energy consumption of the optimal trajectory planned under the law of fifth-order polynomial motion is lower than that of sixth-order polynomial motion. In addition, the experiments also revealed the optimal values of Parameters e and f, which were the parameters of the Lamé curve function. Parameter e can be calculated as half the pick-up span for the minimum mechanical energy consumption, unlike parameter f, whose optimal value depends on specific circumstances such as the pick-and-place coordinates and the pick-up height.
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Research context
OpenAlex topics: Robotic Mechanisms and Dynamics · Robotic Path Planning Algorithms · Advanced Surface Polishing Techniques
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Mechano-Electronic Engineering, Xidian University, Xi’an 710000, China
School of Physics and Electronic Engineering, Xianyang Normal University, Xianyang 712000, China
Funding
National High-Tech Research and Development Program of China · the Educational Reform Project of Xianyang Normal University · the Scientific Research Plan Projects of Shaanxi Education Department
References (41)
Show source-provided references
1. Dynamic feedforward control in decoupling space for a four-degree-of-freedom parallel robot
2. Sohn, J.W., Kim, G.W., and Choi, S.B. (2018). A State-of-the-Art Review on Robots and Medical Devices Using Smart Fluids and Shape Memory Alloys. Appl. Sci., 8.10.3390/app8101928 ↗
3. Nabat, V., François, P., and Poignet, P. (2006, January 9–15). Dynamic Modeling and Identification of Par4, A Very High Speed Parallel Manipulator. Proceedings of the IEEE/RSJ International Conference on Intelligent Robots & Systems, Beijing, China.10.1109/IROS.2006.282533 ↗
4. Kinematic analysis of the X4 translational–rotational parallel robot
5. Singular-Perturbatio-Based Nonlinear Hybrid Control of Redundant Parallel Robot10.1109/TIE.2017.2756587 ↗
6. A stable proportional–proportional integral tracking controller with self-organizing fuzzy-tuned gains for parallel robots
7. Inverse dynamics and trajectory tracking control of a new six degrees of freedom spatial 3-RPRS parallel manipulator10.5194/ms-8-235-2017 ↗
8. Fast genetic algorithm path planner for fixed-wing military UAV using GPU10.1109/TAES.2018.2807558 ↗
9. Pick and place trajectory planning of planar 3-RRR parallel manipulator in the presence of joint clearance10.1017/S0263574714002768 ↗
10. Lin, C.J., and Chen, C.T. (2016). Reconfiguration for the Maximum Dynamic Wrench Capability of a Parallel Robot. Appl. Sci., 6.10.3390/app6030080 ↗
11. Optimal trajectory generation algorithm for serial and parallel manipulators10.1016/j.rcim.2017.04.006 ↗
12. Dynamic point-to-point trajectory planning beyond the static workspace for six-dof cable-suspended parallel robots10.1109/TRO.2018.2794549 ↗
13. Dynamic point-to-point trajectory planning of a three-dof cable-suspended parallel robot10.1109/TRO.2016.2597315 ↗
14. Geometry-based trajectory planning of a 3-3 cable-suspended parallel robot10.1109/TRO.2016.2631591 ↗
15. Chen, Y.D., and Li, L. (2018). Predictable trajectory planning of industrial robots with constraints. Appl. Sci., 8.10.3390/app8122648 ↗
16. A novel trajectory planning scheme for parallel machining Robots enhanced with NURBS curves10.1007/s10846-015-0239-6 ↗
17. A new automatic motion planning algorithm for a 4-degree-of-freedom parallel kinematic manipulator based on the centre sphere method10.1177/0954405414555742 ↗
18. A novel iteration-based controller for hybrid machine systems for trajectory tracking at the end-effector level10.1017/S0263574710000159 ↗
19. Trajectory planning of 3-DOF Delta parallel manipulator10.3901/JME.2016.19.009 ↗
20. Minimum- time trajectory planning and control of a pick-and-place five-bar parallel robot10.1109/TMECH.2014.2318999 ↗
21. Energy-optimal multi-goal motion planning for planar robot manipulators10.1007/s10957-013-0516-0 ↗
22. Petrinec, K., and Kovačić, Z. (2007, January 27–29). Trajectory planning algorithm based on the continuity of jerk. Proceedings of the 15th Mediterranean Conference on Control and Automation, Athens, Greece.10.1109/MED.2007.4433880 ↗
23. Trajectory planning of parallel kinematic manipulators for the maximum dynamic load-carrying capacity10.1007/s11012-015-0308-8 ↗
24. Statistical evaluation of an evolutionary algorithm for minimum time trajectory planning problem for industrial robots10.1007/s00170-016-9050-1 ↗
25. Time-optimal trajectory planning for Delta robot based on quintic Pythagorean-hodograph curves10.1109/ACCESS.2018.2831663 ↗
26. Abe, A. (2013, January 23–26). Minimum energy trajectory planning method for robot manipulator mounted on flexible base. Proceedings of the 9th Asian Control Conference (ASCC), Istanbul, Turkey.10.1109/ASCC.2013.6606088 ↗
27. Application of the redundant servomotor approach to design of path generator with dynamic performance improvement10.1016/j.mechmachtheory.2011.06.003 ↗
28. An underactuated self-reconfigurable robot and the reconfiguration evolution10.1016/j.mechmachtheory.2018.03.004 ↗
29. Minimum energy trajectory for an underwater manipulator and its simple planning method by using a genetic algorithm10.1163/156855399X01044 ↗
30. Dynamic performance analysis of the X4 high-speed pick-and-place parallel robot10.1016/j.rcim.2016.11.003 ↗
31. An approach for smooth trajectory planning of high-speed pick-and-place parallel robots using quintic B-splines10.1016/j.mechmachtheory.2018.04.026 ↗
32. Dynamic trajectory planning for a spatial 3-DoF cable-suspended parallel robot10.1016/j.mechmachtheory.2017.12.023 ↗
33. Polynomial joint angle arm robot motion planning in complex geometrical obstacles10.1016/j.asoc.2012.09.025 ↗
34. Barnard, C.J., Briot, S., and Caro, S. (2012, January 2–4). Trajectory generation for high speed pick and place robots. Proceedings of the ASME 2012 11th Biennial Conference on Engineering Systems Design, Nantes, France.10.1115/ESDA2012-82197 ↗
35. The kinematics, dynamics and control of a flying parallel robot with three quadrotors10.1109/LRA.2017.2774920 ↗
36. Gauthier, J.F., Angeles, J., and Nokleby, S. (2008). Optimization of a Test Trajectory for Scara Systems, Springer.10.1007/978-1-4020-8600-7_24 ↗
37. Energy-Based optimization and experimental validation of the pick-and-place trajectories for the delta parallel robot
38. Grey wolf optimizer10.1016/j.advengsoft.2013.12.007 ↗
39. An optimized grey wolf optimizer based on a mutation operator and eliminating-reconstructing mechanism and its application10.1631/FITEE.1601555 ↗
40. Dynamic global maximum power point tracking of the PV systems under variant partial shading using hybrid GWO-FLC10.1016/j.solener.2018.11.028 ↗
41. Intelligent navigation of mobile robot using grey wolf colony optimization10.1016/j.matpr.2018.06.265 ↗