9 citations · 16 across the 6 of their papers we have counts for
6 papers · 1 filter
Beyond Policy Alignment: Closing the Planning-Learning Loop for Robot Control with Learned World Models
Kowndinya Boyalakuntla, Yuhan Liu, Abdeslam Boularias
Planning with learned world models combines online trajectory optimization with learned value and policy functions for high-dimensional control. Because the planner determines the…
Plan-Conditioned Imitation for Robust Object Retrieval under Self-Occlusion in Dense Clutter
Kowndinya Boyalakuntla, Ajinkya Pawar, Abdeslam Boularias +1
Retrieving objects from dense clutter requires rearrangement during which the manipulator can occlude objects while moving them. Repeated arm withdrawals to restore visibility inte…
KARL: Kalman-Filter Assisted Reinforcement Learner for Dynamic Object Tracking and Grasping
Kowndinya Boyalakuntla, Abdeslam Boularias, Jingjin Yu
We present Kalman-filter Assisted Reinforcement Learner (KARL) for dynamic object tracking and grasping over eye-on-hand (EoH) systems, significantly expanding such systems capabil…
DAP: Diffusion-based Affordance Prediction for Multi-modality Storage
Haonan Chang, Kowndinya Boyalakuntla, Yuhan Liu +3
Solving storage problem: where objects must be accurately placed into containers with precise orientations and positions, presents a distinct challenge that extends beyond traditio…
Context-Aware Entity Grounding with Open-Vocabulary 3D Scene Graphs
Haonan Chang, Kowndinya Boyalakuntla, Shiyang Lu +8
We present an Open-Vocabulary 3D Scene Graph (OVSG), a formal framework for grounding a variety of entities, such as object instances, agents, and regions, with free-form text-base…
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…