Abstract
The problem of trajectory planning is relevant for the proper use of costly robotic systems to mitigate undesirable effects such as vibration and even wear on the mechanical structure of the system. The objective of this study is to design trajectories that are devoid of collision, velocity, acceleration, jerk and snap discontinuities so that the cycle time required to complete the process can be reduced. The trajectory design was constructed for all the six joints, using a 9th order Bezier curve to accommodate the ten boundary conditions required to satisfy the continuity constraints for joints displacement, velocity, acceleration, jerk and snap. The scheme combines the multi-objective genetic algorithm and the multi-objective goal attainment algorithm to solve the problem of total tracking error reduction during arc welding. The use of a hybrid multi-objective algorithm shows an improved average spread, average distance, number of iteration and computational time. Also, it can be concluded from the constraints studied, that the optimal path in terms of the robots dynamic constraints can achieve the expected tracking ability in terms of the optimal joint angles, velocities, acceleration, jerk, snap and torque.
Highlights
Industrial robots (IRs) have changed the face of manufacturing since their debut in the last decades, leading to tremendous advances in efficiency, capability and technology adoption
Unlike the methods as mentioned above, we designed a trajectory for the six joints, using a nonic Bezier curve to accommodate the ten boundary conditions required to satisfy the continuity constraints for joints displacement, velocity, acceleration, jerk and snap
The R-SQUARE values for the joints snap shows significant improvement from 0.46, 0.46, 0.46, 0.14, 0.19 and 0.5, for joints shown in FIGURE 9 (a-f) to 0.77, 0.47, 0.69, 0.42, 0.67 and 0.59, for joints shown in FIGURE 10(a-f), with the use of Hybrid Multi-Objective Genetic Algorithm (HMOGA)
Summary
Industrial robots (IRs) have changed the face of manufacturing since their debut in the last decades, leading to tremendous advances in efficiency, capability and technology adoption. On-line programming refers to physically teaching the robot the required trajectory, through interaction with the aid of a teach pendant or similar device; it has the benefit of being applied to the real-time situation since no testing is required. Optimal trajectory planning plays a vital role in improving efficiency and reduction of the cycle time of the arc welding work-cell, even in the presence of constraints [5]. The snap, as used to denote the derivative of the jerk; is rarely considered as a constraint in trajectory planning of robotic work-cells.
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