Constrained Optimization for Robot Control Application
The benefit of using dynamic optimization for the control of industrial robots has been recognized by the robotics community. However, many of the methods for dynamic optimization use heuristic treatment of physical constraints, limitations on the control inputs, and constraints on the temporal aspect of the motion, common in applications. This talk presents our recent effort to develop a numerically efficient dynamic optimization method which takes physical constraints rigorously into account. The method complements a typical model-based planning approach with an online optimal constrained feedback controller. The method is suitable for real-world application under imperfect model information. Read more about the event and the speakers here.