Topology optimization of industrial robots: Application to a five-bar mechanism

Abstract

Recent works introduced topology optimization in the design of robots, but the proposed methodologies led to a local optimization of the performance. Moreover, most of performance indices used are not in strong relation with easy-to-understand technological requirements. We propose a methodology that is able to perform a topology optimization for robots, valid globally in the workspace or for a set of given trajectories, and which is based on the use of technology-oriented performance criteria. In order to enforce the chosen performance indices to be valid globally, optimal robot configurations or trajectories for which extreme performance will be attained are computed, and iteratively updated. In order to decrease the computational time associated with these performance indices, we exploit the structure of the elastic models in order to reduce their computational complexity. Finally, we use an optimization algorithm called the Linearization Method which gives results in a computational time equivalent to standard topology optimization algorithms, but its implementation is less complex and makes it quite easy to perform modification or improvement. The methodology is applied for the design of a five-bar mechanism. We show that our approach leaded to a robust optimization of the robot performance over the whole workspace.

A Review on Optimization Methods to Enhance Energy Efficiency of Robots

“…The actuating torque and dynamics was optimized by mass redistribution of 2 DOF planar robotic for mass reduction of 32.8% [42]. Recently topology optimization approach adopted to five bar mechanism of an industrial robot and ram structure of friction stir 6 DOF industrial welding robot for decrease the computational time and enhancing energy efficiency by reducing mass by 62.6% respectively [43,44].…”

RobEcolo: Optimal Design of a Wooden Five-Bar Mechanism

“…Based on this physical model, the extraction of some valuable indices to be included into the optimization process must be made, as well as their gradients with respect to the decision variables [27]. These indices and their gradients are inputs of the optimization solvers among which we can mention the Method of Moving Asymptotes (MMA) [28], the Optimality Criteria (OC) (for instance, see [29]), the Projected Gradient [30], the Convex Linearization method (CONLIN) [31]) and the Linearization Method (LM) [32,33].…”

“…e (π E , q)f e (9) in which K e (π E , q) is the reduced stiffness matrix characterizing the overall stiffness of the assembled robot (when variable loads are applied at the endeffector location only) [33,36] which depends of:…”

A Five-Bar Planar Parallel Manipulator with Two End-Effectors

“…Eventhough its simplicity, the five-bar planar parallel manipulator, 5R mechanism for brevity, has been extensively studied approaching issues like inverse-forward kinematics, singularity analysis, optimal workspace, kinematic calibration, topology optimization, robot performance and so on, see for instance [2][3][4][5][6][7]. On the other hand as occur for most parallel manipulators, limited workspace is a drawback of the 5R mechanism, e.g.…”

“…On the other hand as occur for most parallel manipulators, limited workspace is a drawback of the 5R mechanism, e.g. Briot and Goldsztejn [7] proposed a regular dextrous workspace of an optimized 5R mechanism as the area of a rectangle delimited by the workspace boundary and the direct singularities. In that regard the workspace of a 2R open kinematic chain is the area delimited by two concentric circles whose radii depend on the extreme condition folded/unfolded of the serial kinematic chain.…”