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Dynamically evolving algorithm for minimizing the energy consumption of a manipulator

机译：以最小化机械手能耗的动态发展算法

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Global warming and environmental destruction are caused, in part by the mass consumption of energy by industries that use robotic manipulators. Many trajectories planning of the manipulators are determined by giving priority to the operation efficiency such as the operating time and controllability. And it may not be taking the consumption energy into consideration in the trajectory planning. The minimization of the energy under the equation of motion of the manipulator can be reduced to a two-point boundary value problem. This problem can be solved analytically if the equation of motion is linear. However, the equation of motion of a two-links manipulator is non-linear. This paper describes an application of the genetic algorithm based evolution strategy to solve minimizing the consumption energy of a manipulator with non-linear friction at the joints. When applying the genetic algorithm, it is necessary to define the relation between trajectory functions and genes. Fourier cosine series with Mth order are used in this paper. In this minimization problem of the consumption energy, there are many local minimum points due to the non-linearity. A major topic of this paper is to discuss the number of M to increase the accuracy of the solution without falling into the local minimum point. This paper has proposed to change M in the progress of evolution.
机译：全球变暖和环境破坏是由使用机器人操纵器的行业的能源量的大规模消耗。通过优先考虑操作效率，例如操作时间和可控性，确定了许多轨迹规划。在轨迹规划中可能无法考虑消费能量。可以减少操纵器的运动方程下的能量的最小化可以减少到两点边值问题。如果运动方程是线性的，则可以分析地解决该问题。然而，两连杆机械手的运动方程是非线性的。本文介绍了基于遗传算法的应用基于遗传算法的应用，解决了在关节中具有非线性摩擦的机械手的消耗能量。在应用遗传算法时，有必要定义轨迹功能和基因之间的关系。本文使用了傅里叶余弦系列，使用MTH订单。在消耗能量的这种最小化问题中，由于非线性，存在许多局部最小点。本文的主要课题是讨论M的数量，以提高解决方案的准确性而不落入局部最小点。本文提出改变了演变的进展情况。

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