Abstract— This paper provides proof-of-concept that stateof-the-art sampling-based motion planners that are tightly integrated with a physics-based simulator can compute paths th...
Ioan Alexandru Sucan, Jonathan F. Kruse, Mark Yim,...
We present an approach to path planning for humanoid robots that computes dynamically-stable, collision-free trajectories from full-body posture goals. Given a geometric model of t...
James J. Kuffner Jr., Satoshi Kagami, Koichi Nishi...
A key feature of modern optimal planners such as Graphplan and Blackbox is their ability to prune large parts of the search space. Previous Partial Order Causal Link (POCL) planne...
Robots act upon and perceive the world from a particular perspective. It is important to recognize this relativity to perspective if one is not to be overly demanding in specifyin...
Probabilistic Roadmaps (PRM) are a commonly used class of algorithms for robot navigation tasks where obstacles are present in the environment. We examine the situation where the ...