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機器人系統(tǒng)已成為工業(yè)自動化不可或缺的一部分。它迅速進入未來主義、智能空間的概念（如智能家居、輔助康復和醫(yī)療保?。Ｒ虼?，它們一直是控制理論、力學、電子學和系統(tǒng)設計研究人員非常感興趣的話題。一般而言，機器人系統(tǒng)都具有冗余執(zhí)行器，這讓它們有更多的自由度來滿足額外設計需求。然而，求解非線性冗余系統(tǒng)的最優(yōu)解是一項計算量繁重的任務。本次演講描述了一種通過自然啟發(fā)的元啟發(fā)式新穎技術，以數(shù)值有效的方式解決非線性控制問題。這種被稱為BAS的元啟發(fā)式算法是受到天牛自然行為的啟發(fā)，通過對天牛的覓食行為進行了數(shù)字建模。

本次演講將展示如何利用所提出的優(yōu)化框架來解決機械臂的控制問題，如避免障礙、遠程運動中心（RCM）的限制和移動鉸接機器人的控制。它將呈現(xiàn)如何轉換為等效的優(yōu)化問題，并應用控制框架來解決這些問題。數(shù)值結果將證明所提出的控制框架的有效性。

Robotic systems have become an integral part of industrial automation and rapidly finding their way into the concept of futuristic, intelligent spaces, i.e., smart homes, assistive rehabilitation, and healthcare. As such, they have been a topic of great interest for researchers from control theory, mechanics, electronics, and system design. Usually, robotic systems have redundant actuators, giving them an extra degree of freedom to meet the additional design requirement. However, solving a nonlinear redundant system for an optimal solution is a computationally expensive task. This talk describes novel nature-inspired metaheuristic techniques to solve the nonlinear control problem in a numerically efficient manner. The metaheuristic algorithm, called BAS, is inspired by the natural behavior of beetles and mathematically model their food foraging behavior.

This talk shows how the proposed optimization framework can be used to solve several control problems for robotic arms, i.e., obstacle avoidance, Remote Centre of Motion (RCM) constraints, and control of mobile articulated robots. It will be shown how the above-mentioned control problem can be converted to equivalent optimization problems, and the control framework can be applied to solve those problems. The numerical results will be shown to demonstrate the efficacy of the proposed control framework.