11 citations · 31 across the 6 of their papers we have counts for
6 papers
Learning to Assemble Geometric Shapes
Jinhwi Lee, Jungtaek Kim, Hyunsoo Chung +2
Assembling parts into an object is a combinatorial problem that arises in a variety of contexts in the real world and involves numerous applications in science and engineering. Pre…
Brick-by-Brick: Combinatorial Construction with Deep Reinforcement Learning
Hyunsoo Chung, Jungtaek Kim, Boris Knyazev +4
Discovering a solution in a combinatorial space is prevalent in many real-world problems but it is also challenging due to diverse complex constraints and the vast number of possib…
Fast and resilient manipulation planning for target retrieval in clutter
Changjoo Nam, Jinhwi Lee, Sang Hun Cheong +2
This paper presents a task and motion planning (TAMP) framework for a robotic manipulator in order to retrieve a target object from clutter. We consider a configuration of objects…
Where to relocate?: Object rearrangement inside cluttered and confined environments for robotic manipulation
Sang Hun Cheong, Brian Y. Cho, Jinhwi Lee +2
We present an algorithm determining where to relocate objects inside a cluttered and confined space while rearranging objects to retrieve a target object. Although methods that dec…
Planning for target retrieval using a robotic manipulator in cluttered and occluded environments
Changjoo Nam, Jinhwi Lee, Younggil Cho +3
This paper presents planning algorithms for a robotic manipulator with a fixed base in order to grasp a target object in cluttered environments. We consider a configuration of obje…
Efficient Obstacle Rearrangement for Object Manipulation Tasks in Cluttered Environments
Jinhwi Lee, Younggil Cho, Changjoo Nam +2
We present an algorithm that produces a plan for relocating obstacles in order to grasp a target in clutter by a robotic manipulator without collisions. We consider configurations…