Over the last decade, the development of robot motion planning algorithms to solve complex geometric problems has not only contributed to advances in industrial automation and autonomous exploration, but also to a number of diverse fields such as graphics animation and computational structural biology.


This talk will discuss the state of the
art of sampling-based motion planning with emphasis on work for systems with increased physical realism.


Recent advances in planning for hybrid
systems will be described, as well as the challenges of combining formal logic and planning for creating safe and reliable robotic systems.
The talk will also demonstrate how the experience gained through robotics planning has led to algorithmic tools for analyzing the flexibility and interactions of molecules for the discovery of new medicines.