On the Optimization of Robotic Manipulator Trajectories With Bounded Joint Actuators or Joint Kinetic Loads Considered as Control Variables

Bessonnet, Guy; Lallemand, J.P.

doi:10.1115/1.2899287

Cited by 7 publications

(7 citation statements)

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“…[14] marks an intermediate step between [13] and [15]. [16] further improves the efficiency of the approach by selecting a set of joint actuators and joint kinetic loads as constrained control variables.…”

Section: Point-to-point Motion and Related Problemsmentioning

confidence: 99%

Optimal Control of Rigid‐Link Manipulators by Indirect Methods

Callies¹,

Rentrop

2008

GAMM-Mitteilungen

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The present paper is a survey and research paper on the treatment of optimal control problems of rigid-link manipulators by indirect methods. Maximum Principle based approaches provide an excellent tool to calculate optimal reference trajectories for multi-link manipulators with high accuracy. Their major drawback was the need to explicitly formulate the complicated system of adjoint differential equations and to apply the full apparatus of optimal control theory. This is necessary in order to convert the optimal control problem into a piecewise defined, nonlinear multi-point boundary value problem. An accurate and efficient access to first-and higher-order derivatives is crucial. The approach described in this paper allows it to generate all the derivative information recursively and simultaneously with the recursive formulation of the equations of motion. Nonlinear state and control constraints are treated without any simplifications by transforming them into sequences of systems of linear equations. By these means, the modeling of the complete optimal control problem and the accompanying boundary value problem is automated to a great extent. The fast numerical solution is by the advanced multiple shooting method JANUS.

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Section: Point-to-point Motion and Related Problemsmentioning

confidence: 99%

Optimal Control of Rigid‐Link Manipulators by Indirect Methods

Callies¹,

Rentrop

2008

GAMM-Mitteilungen

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“…Step 1: Generate a trajectory candidate (q,(), i=l, n), by selecting randomly J, and Jb in the interval ]0, 1 [ and (14) applying (17) or (18).…”

Section: General Strategy Of Resolutionmentioning

confidence: 99%

Suboptimal Trajectory Generation for Industrial Robots using Trapezoidal Velocity Profiles

Chettibi¹,

Haddad²,

Lehtihet³

2006

2006 IEEE/RSJ International Conference on Intelligent Robots and Systems

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because the dynamics is simply described by the inverse dynamic model.In the present paper, we propose a new and simple direct method able to generate suboptimal trajectories for robotic manipulators minimizing the transfer time T and verifying imposed kinodynamic constraints. It can be seen as a variant of DCPM. This method is based first on the dissociation of the search of the optimal transfer time T from that of the other optimal motion parameters. This allows us to express the kinodynamic constraints as bounds on admissible values of T. Then, normalized trapezoidal velocity profiles (TVP) are used to generate trajectory profile candidates. Finally, a stochastic optimization method is used to find the best trajectory profile leading to the best approximation of the optimal time motion T. This work is motivated by the following:* The simplicity of the classical TVP and its large use in the industrial context. * The reduced number of optimization parameters which allows solving the problem in quasi real time. * The obtained trajectory can be implemented on existing robot controllers.

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“…The high level of energy consumption is typically caused by jerky motions of robots. Many research efforts addressed design optimization [2,3], path planning [4][5][6][7][8][9][10][11][12], and minimizing joints' torques [13][14][15][16].…”

Section: Introductionmentioning

confidence: 99%

Multivariable Extremum Seeking for Joint-Space Trajectory Optimization of a High-Degrees-of-Freedom Robot

Bagheri

Krstić

2018

Journal of Dynamic Systems, Measurement, and Control

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In this paper, a novel analytical coupled trajectory optimization of a seven degrees-of-freedom (7DOF) Baxter manipulator utilizing extremum seeking (ES) approach is presented. The robotic manipulators are used in network-based industrial units, and even homes, by expending a significant lumped amount of energy, and therefore, optimal trajectories need to be generated to address efficiency issues. These robots are typically operated for thousands of cycles resulting in a considerable cost of operation. First, coupled dynamic equations are derived using the Lagrangian method and experimentally validated to examine the accuracy of the model. Then, global design sensitivity analysis is performed to investigate the effects of changes of optimization variables on the cost function leading to select the most effective ones. We examine a discrete-time multivariable gradient-based ES scheme enforcing operational time and torque saturation constraints in order to minimize the lumped amount of energy consumed in a path given; therefore, time-energy optimization would not be the immediate focus of this research effort. The results are compared with those of a global heuristic genetic algorithm (GA) to discuss the locality/globality of optimal solutions. Finally, the optimal trajectory is experimentally implemented to be thoroughly compared with the inefficient one. The results reveal that the proposed scheme yields the minimum energy consumption in addition to overcoming the robot's jerky motion observed in an inefficient path.

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On the Optimization of Robotic Manipulator Trajectories With Bounded Joint Actuators or Joint Kinetic Loads Considered as Control Variables

Cited by 7 publications

References 0 publications

Optimal Control of Rigid‐Link Manipulators by Indirect Methods

Optimal Control of Rigid‐Link Manipulators by Indirect Methods

Suboptimal Trajectory Generation for Industrial Robots using Trapezoidal Velocity Profiles

Multivariable Extremum Seeking for Joint-Space Trajectory Optimization of a High-Degrees-of-Freedom Robot

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