Control theory is an important cornerstone of the robotics field and is considered a fundamental subject in an undergraduate and postgraduate robotics curriculum. Furthermore, project-based learning has shown significant benefits in engineering domains, specifically in interdisciplinary fields such as robotics which require hands-on experience to master the discipline adequately. However, designing a project-based learning experience to teach control theory in a hands-on setting can be challenging, due to the rigor of mathematical concepts involved in the subject. Moreover, access to reliable hardware required for a robotics control lab, including the robots, sensors, interfaces, and measurement instruments, may not be feasible in developing countries and even many academic institutions in the US. The current paper presents a set of six project-based assignments for an advanced postgraduate Robot Control course. The assignments leverage the Robot Operating System (ROS), an open-source set of tools, libraries, and software, which is a de facto standard for the development of robotics applications. The use of ROS, along with its physics engine simulation framework, Gazebo, provides a hands-on robotics experience equivalent to working with real hardware. Learning outcomes include: i) theoretical analysis of linear and nonlinear dynamical systems, ii) formulation and implementation of advanced model-based robot control algorithms using classical and modern control theory, and iii) programming and performance evaluation of robotic systems on physics engine robot simulators. Course evaluations and student surveys demonstrate that the proposed project-based assignments successfully bridge the gap between theory and practice, and facilitate learning of control theory concepts and state-of-the-art robotics techniques through a hands-on approach.

翻译：控制理论是机器人技术领域的重要基石，被视为本科及研究生机器人课程体系中的基础学科。同时，基于项目的学习模式在工程领域展现出显著优势，特别在机器人这类需要实操经验才能充分掌握的交叉学科中尤为突出。然而，由于该学科涉及严谨的数学概念，设计基于项目的实践性控制理论学习体验颇具挑战。此外，在发展中国家甚至美国许多学术机构中，构建机器人控制实验室所需的高可靠性硬件（包括机器人、传感器、接口和测量仪器）往往难以实现。本文针对高级研究生机器人控制课程提出六组项目式作业方案。这些作业依托机器人操作系统（ROS）这一开源工具、库及软件集合（该平台已成为机器人应用开发的事实标准），并结合其物理引擎仿真框架Gazebo，可提供与真实硬件操作等效的实践体验。预期学习成果包括：i) 线性及非线性动力系统的理论分析，ii) 基于经典与现代控制理论的先进模型预测机器人控制算法的设计与实现，iii) 在物理引擎机器人模拟器中的编程与系统性能评估。课程评估与学生反馈表明，所提出的项目式作业有效弥合了理论与实践的鸿沟，通过实践途径促进了对控制理论概念与前沿机器人技术的掌握。