9 citations · 14 across the 5 of their papers we have counts for
5 papers
Resolution Complete In-Place Object Retrieval given Known Object Models
Daniel Nakhimovich, Yinglong Miao, Kostas E. Bekris
This work proposes a robot task planning framework for retrieving a target object in a confined workspace among multiple stacked objects that obstruct the target. The robot can use…
Effective and Robust Non-Prehensile Manipulation via Persistent Homology Guided Monte-Carlo Tree Search
Ewerton R. Vieira, Kai Gao, Daniel Nakhimovich +2
Performing object retrieval in real-world workspaces must tackle challenges including \emph{uncertainty} and \emph{clutter}. One option is to apply prehensile operations, which can…
Persistent Homology for Effective Non-Prehensile Manipulation
Ewerton R. Vieira, Daniel Nakhimovich, Kai Gao +3
This work explores the use of topological tools for achieving effective non-prehensile manipulation in cluttered, constrained workspaces. In particular, it proposes the use of pers…
Uniform Object Rearrangement: From Complete Monotone Primitives to Efficient Non-Monotone Informed Search
Rui Wang, Kai Gao, Daniel Nakhimovich +2
Object rearrangement is a widely-applicable and challenging task for robots. Geometric constraints must be carefully examined to avoid collisions and combinatorial issues arise as…
Pushing the Boundaries of Asymptotic Optimality in Integrated Task and Motion Planning
Rahul Shome, Daniel Nakhimovich, Kostas E. Bekris
Integrated task and motion planning problems describe a multi-modal state space, which is often abstracted as a set of smooth manifolds that are connected via sets of transitions s…