It covers basic algorithm design techniques such as divide and conquer, dynamic programming, and greedy algorithms. It concludes with a brief introduction to intractability (NP-completeness) .

Students interested in further readings can look at the books below: D Bertsimas and J N Tsitsiklis, Introduction to Linear Optimization, Athena Scientific, 1997. S Boyd and L Vandenberghe, Convex ...

Throughout, the authors balance the impact of hardware (mechanism, sensor, actuator) and software (algorithms) in teaching robot autonomy. Rigorous and tested in the classroom, Introduction to ...