Hours:
24 hours (6 credits)

Room:
From remote by using Microsoft Teams. The link will be sent in due time to all students who registered to the seminar.

To register to the course, click here

Short Abstract:
The availability of an unprecedented level of computational power opens a whole new range of possibilities in several fields. This is strongly impacting the way to plan and control the motion of robots. This course will provide an approach to exploit the full potential of these new tools starting from the calculus of variations theory and then showing how to properly translate an optimal control problem into an optimization program. Hence an overview of the state-of-the-art optimization algorithms (and tools) will be given highlighting the link between different algorithms and problems. Finally examples and open problems will be discussed.

Course Contents in brief:

1. Introduction (0.5 h)
2. Elements of Calculus of Variations (3 h)
3. From Optimal Control to Optimization (3.5 h)
4. Optimization Problems (3.5 h)
5. Deterministic Optimization Algorithms (3.5 h)
6. Tools, Solvers and the Decision Tree (3.5 h)
7. Examples (3.5 h)
8. Open Problems in Motion Planning and Control of Robots (3 h)

Schedule:

Monday 27 – Friday 31 July 2020