Over the last decade, robot motion planning algorithms have been developed
to solve complex geometric problems and have contributed to advances in
industrial automation and autonomous exploration, but also in diverse fields
such as graphics animation and computational structural biology.
This talk begins by reviewing the state of the art in sampling-based motion
planning with emphasis on work for systems with increased physical realism.
Then 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 systems.
