KEY TOPICS COVERED:

• Mathematical Foundations: Dynamical system safety analysis, correctness guarantees, and formal safety verification methods
• Robotic Decision Making: Algorithmic approaches for safety-critical environments with focus on reliability and robustness
• Safe Robot Learning: Learning under uncertainty, model uncertainty handling, and safety assurance for vision-based perception systems

CURRICULUM HIGHLIGHTS:

• System Modeling: Time domain and transfer function models for comprehensive system analysis and controller synthesis
• System Analysis: SISO analysis in frequency domain, BIBO and asymptotic stability, transient and steady-state response, Bode plots
• Controller Design: Feedback systems, closed-loop analysis, explicit loop shaping, disturbance rejection, P/PD/PID controllers

LEARNING OBJECTIVES:

• Mathematical Foundations: Introduction to fundamental linear algebra concepts and theoretical framework
• Proof Techniques: Development of analytical skills for proving mathematical facts using linear algebra principles
• Real-World Applications: Application of linear algebra tools to solve concrete engineering problems
• Computational Skills: MATLAB programming for implementing linear algebra solutions in practical scenarios