Robots and in particular humanoid robots are extremely complicated dynamical systems for which the generation of behaviors is no easy task, since the number of parameters to tune for a behavior is very high. But the challenges waiting for today’s robots require them to automatically generate and control a wide range of behaviors in order to be more flexible and adaptive to changing environments. Optimization or optimal control offers an interesting way to generate behaviors automatically based on elementary principles (cost functions, constraints). Moore’s law as well as recent developments in optimization algorithms and in particular real-time optimization make a wider application of algorithmic optimization a realistic option even for real-time control in complex robotic applications in the near future.
This interdisciplinary scope includes establishing bridges to the mathematical optimization community as well as to the field of biomechanics (to learn from biology and to identify optimality criteria) and to computer graphics (for promising optimization approaches on physically realistic models).
