CAREER: Sensor Management in Intelligent Motion Control Systems and Learning About Intelligent Machines Using a Problem Based Approach

本研究探讨了智能运动控制系统中的传感器管理，其主要目标是描述和评估关注传感器的数学模型。一个系统模型和控制拓扑结构，反映了硬件的性能，如计算延迟和通信限制，使用。 对设备的关注量可以通过选择反馈增益和分配给设备的通信总线访问程度来解释。 使用此模型的控制合成将解决诸如哪些传感器应用于任务，设备之间需要多大程度的协调以及系统稳定等问题。控制设计方法将应用于机器人应用。这项研究的成功完成将使复杂机器人系统的设计者能够利用 选择传感器的正式程序 和 确定电机子系统之间所需的或足够的协调，同时仍然确保系统稳定性。 该项目的另一个目标是开发智能机器领域的课程，为机械工程师提供跨学科技能，提高学生解决工程问题的能力。 这两个目标将通过一个动手在机器人本科课程使用基于问题的学习来解决 (PBL)教学方法 使用PBL， 学生识别解决问题所需的理论，学习理论，并应用它。 因此，学生探索相关的科目，因为他们看到他们的需要。机器人课程，从多个学科的材料，适合这种方法。 一 研究生水平的智能系统课程也将开发。

This research explores sensor management in intelligent motion control systems with the main objective of describing and evaluating a mathematical model of what it means to pay attention to a sensor. A system model and control topology that reflects properties of the hardware, such as computation delays and communication limitations, is used. The amount of attention devoted to a device can be interpretated through the selection of feedback gains and the degree of communication bus access allocated to the device. Control synthesis with this model will address questions such as which sensors should be used for a task, what degree of coordination between devices is required, and is the system stable? The control design methodology will be applied to robotic applications. Successful completion of this research will enable designers of complex robotic systems to utilize a formal procedure in selecting sensors and in determining the required, or sufficient, coordination between motor subsystems, while still ensuring system stability. The other objective of this project is to develop curriculum in the area of intelligent machines, providing mechanical engineers with interdisciplinary skills and improving students' engineering problem solving skills. Both goals will be addressed through a hands-on undergraduate course in Robotics using a problem based learning (PBL) teaching methodology. Using PBL, students identify the theory required to solve a problem, learn the theory, and apply it. Thus students explore the relevant subjects as they see the need for them. A robotics course, with material from multiple disciplines, is suited to this approach. A graduate level Intelligent Systems course will also be developed.