Optimal trajectory generation of an industrial welding robot with kinematic and dynamic constraints

Author(s):  
Amruta Rout ◽  
Deepak Bbvl ◽  
Bibhuti B. Biswal

Purpose This paper aims to present an optimal trajectory planning for industrial MOTOMAN MA1440A gas metal arc welding system. A new and efficient evolutionary algorithm, enhanced multi-objective teaching learning-based optimization (EMOTLBO) method, i.e. TLBO with non-dominated sorting approach has been proposed to obtain the optimal joint trajectory for the defined weld seam path. Design/methodology/approach The joint trajectory of the welding robot need to be computed in an optimal manner for proper torch orientation, smooth travel of the robot along the weld path and for achieving higher positional accuracy. This can be achieved by limiting the kinematic and dynamic variations of the robot joints like joint jerks, squared acceleration and torque induced in the joints while travel of the robot along the weld path. Also, the robot travel should be done within minimum possible time for maintaining productivity. This leads to a multi-objective optimization problem which needs to be solved for maintaining proper orientation of the robot end effector. EMOTLBO has been proposed to obtain the Pareto front consisting of optimal solutions. The fuzzy membership function has been used to obtain the optimal solution from the Pareto front with best trade-off between objectives. Findings The proposed method has been implanted in MATLAB R2017a for simulation results. The joint positions have been used to program the robot for performing welding operation along the weld seam. From the simulation and experimental results, it can be concluded that the proposed approach can be effectively used for optimal trajectory planning of MOTOMAN MA 1440 A arc welding robot system as a very smooth and uniform weld bead has been obtained with maximum weld quality. Originality/value In this paper, a novel approach for optimal trajectory planning welding arc robot has been performed. Though trajectory planning of industrial robots has been done before, it has not been done yet for welding robot. The objectives are formulated taking in consideration of requirement of welding process like minimization of joint jerks and torques induced during welding operation due to travel of robot with the effect of arc spatter, minimization of squared acceleration for maintaining constant joint velocity and finally minimization of total travel time for maintaining productivity.

2020 ◽  
Vol 43 ◽  
pp. 527-534 ◽  
Author(s):  
Xuemei Liu ◽  
Chengrong Qiu ◽  
Qingfei Zeng ◽  
Aiping Li ◽  
Nan Xie

Robotica ◽  
2021 ◽  
pp. 1-19
Author(s):  
Xiaofu Zhang ◽  
Guanglin Shi

Abstract This paper presents a trajectory planning method based on multi-objective optimization, including time optimal and jerk optimal for the manipulators in the presence of obstacles. The proposed method generates a trajectory configuration in the joint space with kinematic and obstacle constraints using quintic B-spline. Gilbert–Johnson–Keerthi detecting algorithm is utilized to detect whether there is a collision and obtain the minimum distance between the manipulator and obstacles. The degree of constraint violations is introduced to redefine the Pareto domination, and the constrained multi-objective particle swarm algorithm (CMOPSO) is adopted to solve the time-jerk optimization problem. Finally, the Z-type fuzzy membership function is proposed to select the best optimal solution in the Pareto front obtained by CMOPSO. Test results show the effectiveness of the proposed method.


Author(s):  
Xueshan Gao ◽  
Yu Mu ◽  
Yongzhuo Gao

Purpose The purpose of this paper is to propose a method of optimal trajectory planning for robotic manipulators that applies an improved teaching-learning-based optimization (ITLBO) algorithm. Design/methodology/approach The ITLBO algorithm possesses better ability to escape from the local optimum by integrating the original TLBO with variable neighborhood search. The trajectory of robotic manipulators complying with the kinematical constraints is constructed by fifth-order B-spline curves. The objective function to be minimized is execution time of the trajectory. Findings Experimental results with a 6-DOF robotic manipulator applied to surface polishing of metallic workpiece verify the effectiveness of the method. Originality/value The presented ITLBO algorithm is more efficient than the original TLBO algorithm and its variants. It can be applied to any robotic manipulators to generate time-optimal trajectories.


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