3 citations · 12 across the 19 of their papers we have counts for
5 papers · 1 filter
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…
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…
Optimal and Stable Multi-Layer Object Rearrangement on a Tabletop
Andy Xu, Kai Gao, Si Wei Feng +1
Object rearrangement is a fundamental sub-task in accomplishing a great many physical tasks. As such, effectively executing rearrangement is an important skill for intelligent robo…
Effectively Rearranging Heterogeneous Objects on Cluttered Tabletops
Kai Gao, Justin Yu, Tanay Sandeep Punjabi +1
Effectively rearranging heterogeneous objects constitutes a high-utility skill that an intelligent robot should master. Whereas significant work has been devoted to the grasp synth…
Minimizing Running Buffers for Tabletop Object Rearrangement: Complexity, Fast Algorithms, and Applications
Kai Gao, Si Wei Feng, Baichuan Huang +1
For rearranging objects on tabletops with overhand grasps, temporarily relocating objects to some buffer space may be necessary. This raises the natural question of how many simult…