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

机译：具有运动和动态约束的工业焊接机器人的最佳轨迹生成

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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.
机译：目的本文旨在为工业马赛克MA1440A气体金属弧焊系统提供最佳的轨迹规划。已经提出了一种新的高效的进化算法，增强的基于多目标教学的优化（EMECLLBO）方法，即具有非主导排序方法的TLBO，以获得定义的焊缝路径的最佳关节轨迹。设计/方法/方法需要以最佳的方式计算焊接机器人的关节轨迹，以便适当的割炬方向，沿着焊接路径的机器人的平滑行程和实现更高的位置精度。这可以通过限制机器人关节的运动和动态变化，如关节锯齿，平方加速度和在接头中诱导的同时沿着焊接路径行进机器人的扭矩。此外，机器人旅行应该在最低可能的时间内进行，以保持生产率。这导致了需要解决的多目标优化问题，以维持机器人末端执行器的正确取向。 EndleLBO已提议获得由最佳解决方案组成的帕累托前线。模糊会员函数已被用于从帕累托前面获得最佳解决方案，在目标之间获得最佳权衡。发现该方法已植入MATLAB R2017A进行仿真结果。联合位置已被用于编程机器人以沿焊缝进行焊接操作。从模拟和实验结果来看，可以得出结论，所提出的方法可以有效地用于MOTOMAN MA 1440的最佳轨迹规划，通过最大焊接质量获得了弧焊机器人系统作为非常光滑和均匀的焊缝。本文的原创性/值，已经进行了一种用于最佳轨迹规划焊接弧机器人的新方法。虽然以前已经完成了工业机器人的轨迹规划，但它尚未为焊接机器人进行。考虑到焊接工艺的要求，如机器人的行驶，以焊接运行在焊接运行中引起的焊接和扭矩的最小化的要求制定了目的，以施加弧溅，最小化平方加速度，以保持恒定的关节速度，最终排除总旅行保持生产力的时间。

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