Abstract
This paper addresses a problem of a continuous path planning of a redundant manipulator where an end-effector needs to follow a desired path. Based on a geometrical analysis, feasible postures of a self-motion are mapped into an interval so that there will be an angle domain boundary and a redundancy resolution to track the desired path lies within this boundary. To choose a best solution among many possible solutions, meta-heuristic optimizations, namely, a Genetic Algorithm (GA), a Particle Swarm Optimization (PSO), and a Grey Wolf Optimizer (GWO) will be employed with an optimization objective to minimize a joint angle travelling distance. To achieve n-connectivity of sampling points, the angle domain trajectories are modelled using a sinusoidal function generated inside the angle domain boundary. A complex geometrical path obtained from Bezier and algebraic curves are used as the traced path that should be followed by a 3-Degree of Freedom (DOF) arm robot manipulator and a hyper-redundant manipulator. The path from the PSO yields better results than that of the GA and GWO.
Highlights
Nowadays, researches in the robotic field are focusing on the use of robot to substitute human operator jobs in dangerous environment because it involves the high risk for human safety
Different with a point-to-point path planning where the end-effector path is free to be chosen, in the continuous path planning, the arm robot manipulator needs to move along the prescribed end-effector path
This paper considers planar redundant and planar hyperredundant manipulators where the path planning can be formulated as the optimization problem as follows: Objective:
Summary
Researches in the robotic field are focusing on the use of robot to substitute human operator jobs in dangerous environment because it involves the high risk for human safety. Human operator is usually still used due to the task is conducted in a difficult environment involving a very complex geometrical path. The path planning to track the prescribed path is very important research to be conducted toward the automation in the manufacturing industry involving complex geometrical path. Using the manipulator to track a complex geometry in the manufacturing industry, the goal is to achieve the high precision as well as satisfy the optimality criteria so that the production efficiency can be improved. For very challenging environmental conditions, an off-line tracking algorithm is considered as an efficient approach because an online path planning is only available for very simple tasks such as a pick and place [1]. The continuous path planning needs to solve an Inverse Kinematic (IK) problem for the entire traced path
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