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pro vyhledávání: '"Nakhimovich, Daniel"'
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 prehensile picking and in-workspace placing actions. The method assum
Externí odkaz:
http://arxiv.org/abs/2303.14562
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 be time consuming in highly-cluttered scenarios. On the other hand, n
Externí odkaz:
http://arxiv.org/abs/2210.01283
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 persistent homology as a guiding principle in identifying the appropriate
Externí odkaz:
http://arxiv.org/abs/2202.02937
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 the number of objects increases. This work studies the algorithmic str
Externí odkaz:
http://arxiv.org/abs/2101.12241
Publikováno v:
Algorithmic Foundations of Robotics XIV (2021) 467-484
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 states. One approach to solving such problems is to sample reachable st
Externí odkaz:
http://arxiv.org/abs/1903.01006
Akademický článek
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Performing object retrieval tasks in messy real-world workspaces involves the challenges of \emph{uncertainty} and \emph{clutter}. One option is to solve retrieval problems via a sequence of prehensile pick-n-place operations, which can be computatio
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f9545060ba9b97d7485c7aaeef69f46f