机器人系统已成为工业自动化不可或缺的一部分。它迅速进入未来主义、智能空间的概念（如智能家居、辅助康复和医疗保健）。因此，它们一直是控制理论、力学、电子学和系统设计研究人员非常感兴趣的话题。一般而言，机器人系统都具有冗余执行器，这让它们有更多的自由度来满足额外设计需求。然而，求解非线性冗余系统的最优解是一项计算量繁重的任务。本次演讲描述了一种通过自然启发的元启发式新颖技术，以数值有效的方式解决非线性控制问题。这种被称为BAS的元启发式算法是受到天牛自然行为的启发，通过对天牛的觅食行为进行了数字建模。

本次演讲将展示如何利用所提出的优化框架来解决机械臂的控制问题，如避免障碍、远程运动中心（RCM）的限制和移动铰接机器人的控制。它将呈现如何转换为等效的优化问题，并应用控制框架来解决这些问题。数值结果将证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.