Nature inspired algorithms to optimize robot workcell layouts

Method for Robot Manipulator Joint Wear Reduction by Finding the Optimal Robot Placement in a Robotic Cell

We describe a method for robotic cell optimization by changing the placement of the robot manipulator within the cell in applications with a fixed end-point trajectory. The goal is to reduce the overall robot joint wear and to prevent uneven joint wear when one or several joints are stressed more than the other joints. Joint wear is approximated by calculating the integral of the mechanical work of each joint during the whole trajectory, which depends on the joint angular velocity and torque. The method relies on using a dynamic simulation for the evaluation of the torques and velocities in robot joints for individual robot positions. Verification of the method was performed using CoppeliaSim and a laboratory robotic cell with the collaborative robot UR3. The results confirmed that, with proper robot base placement, the overall wear of the joints of a robotic arm could be reduced from 22% to 53% depending on the trajectory.

Construction and Layout of Coordinated Multirobots System Based on Parallel Thought

Aiming at the problems that are the construction and the layout optimization of the coordinated multirobots system, the concept of an equivalent parallel robot (EPR) is proposed based on parallel thought in this paper. That is, each robot is regarded as a branched chain of the EPR in coordination. Thus, it can be converted into the problem for the type synthesis and the layout of the parallel robot. Firstly, the definition of robotic characteristic (C) set and the corresponding operational rule are given. Then, the minimum occupied area, cycle time, and condition number are used as the optimized objectives. The weight ratio is used to express the importance of the three objectives to meet the requirements of different scenes. Afterwards, based on the theory of C set, the three translational (3T) operational requirements that can be extended to other degree of freedom (DOF) are analyzed. Finally, the feasibility of the proposed methods is verified by the DOF analysis and simulation experiment. Moreover, the multiobjective layout problem is optimized based on the artificial bee colony (ABC) algorithm. The results show that the constructed robot combinations and the layout optimization method are satisfactory.