6 papers · 1 filter
MuST: Multi-Head Skill Transformer for Long-Horizon Dexterous Manipulation with Skill Progress
Kai Gao, Fan Wang, Erica Aduh +2
Robot picking and packing tasks require dexterous manipulation skills, such as rearranging objects to establish a good grasping pose, or placing and pushing items to achieve tight…
Tabletop Object Rearrangement: Structure, Complexity, and Efficient Combinatorial Search-Based Solutions
Kai Gao
This thesis provides an in-depth structural analysis and efficient algorithmic solutions for tabletop object rearrangement with overhand grasps (TORO), a foundational task in advan…
ORLA*: Mobile Manipulator-Based Object Rearrangement with Lazy A Star
Kai Gao, Zhaxizhuoma, Yan Ding +2
Effectively performing object rearrangement is an essential skill for mobile manipulators, e.g., setting up a dinner table or organizing a desk. A key challenge in such problems is…
LGMCTS: Language-Guided Monte-Carlo Tree Search for Executable Semantic Object Rearrangement
Haonan Chang, Kai Gao, Kowndinya Boyalakuntla +5
We introduce a novel approach to the executable semantic object rearrangement problem. In this challenge, a robot seeks to create an actionable plan that rearranges objects within…
Toward Holistic Planning and Control Optimization for Dual-Arm Rearrangement
Kai Gao, Zihe Ye, Duo Zhang +2
Long-horizon task and motion planning (TAMP) is notoriously difficult to solve, let alone optimally, due to the tight coupling between the interleaved (discrete) task and (continuo…
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…