3 citations · 12 across the 19 of their papers we have counts for
19 papers
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…
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…
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…
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…
On the Utility of Buffers in Pick-n-Swap Based Lattice Rearrangement
Kai Gao, Jingjin Yu
We investigate the utility of employing multiple buffers in solving a class of rearrangement problems with pick-n-swap manipulation primitives. In this problem, objects stored rand…
Toward Efficient Task Planning for Dual-Arm Tabletop Object Rearrangement
Kai Gao, Jingjin Yu
We investigate the problem of coordinating two robot arms to solve non-monotone tabletop multi-object rearrangement tasks. In a non-monotone rearrangement task, complex object-obje…
Lazy Rearrangement Planning in Confined Spaces
Rui Wang, Kai Gao, Jingjin Yu +1
Object rearrangement is important for many applications but remains challenging, especially in confined spaces, such as shelves, where objects cannot be accessed from above and the…
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…
Fast High-Quality Tabletop Rearrangement in Bounded Workspace
Kai Gao, Darren Lau, Baichuan Huang +2
In this paper, we examine the problem of rearranging many objects on a tabletop in a cluttered setting using overhand grasps. Efficient solutions for the problem, which capture a c…
Capacitated Vehicle Routing with Target Geometric Constraints
Kai Gao, Jingjin Yu
We investigate the capacitated vehicle routing problem (CVRP) under a robotics context, where a vehicle with limited payload must complete delivery (or pickup) tasks to serve a set…
On Minimizing the Number of Running Buffers for Tabletop Rearrangement
Kai Gao, Si Wei Feng, Jingjin Yu
For tabletop rearrangement problems with overhand grasps, storage space outside the tabletop workspace, or buffers, can temporarily hold objects which greatly facilitates the resol…
Sensor Placement for Globally Optimal Coverage of 3D-Embedded Surfaces
Si Wei Feng, Kai Gao, Jie Gong +1
We carry out a structural and algorithmic study of a mobile sensor coverage optimization problem targeting 2D surfaces embedded in a 3D workspace. The investigated settings model m…
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…
Efficient Algorithms for Optimal Perimeter Guarding
Si Wei Feng, Shuai D. Han, Kai Gao +1
We investigate the problem of optimally assigning a large number of robots (or other types of autonomous agents) to guard the perimeters of closed 2D regions, where the perimeter o…