8 citations · 12 across the 8 of their papers we have counts for
8 papers
STAR: A Foundation Model-driven Framework for Robust Task Planning and Failure Recovery in Robotic Systems
Md Sadman Sakib, Yu Sun
Modern robotic systems, deployed across domains from industrial automation to domestic assistance, face a critical challenge: executing tasks with precision and adaptability in dyn…
Consolidating Trees of Robotic Plans Generated Using Large Language Models to Improve Reliability
Md Sadman Sakib, Yu Sun
The inherent probabilistic nature of Large Language Models (LLMs) introduces an element of unpredictability, raising concerns about potential discrepancies in their output. This pa…
From Cooking Recipes to Robot Task Trees -- Improving Planning Correctness and Task Efficiency by Leveraging LLMs with a Knowledge Network
Md Sadman Sakib, Yu Sun
Task planning for robotic cooking involves generating a sequence of actions for a robot to prepare a meal successfully. This paper introduces a novel task tree generation pipeline…
Approximate Task Tree Retrieval in a Knowledge Network for Robotic Cooking
Md. Sadman Sakib, David Paulius, Yu Sun
Flexible task planning continues to pose a difficult challenge for robots, where a robot is unable to creatively adapt their task plans to new or unseen problems, which is mainly d…
Functional Task Tree Generation from a Knowledge Graph to Solve Unseen Problems
Md. Sadman Sakib, David Paulius, Yu Sun
A major component for developing intelligent and autonomous robots is a suitable knowledge representation, from which a robot can acquire knowledge about its actions or world. Howe…
Evaluating Recipes Generated from Functional Object-Oriented Network
Md Sadman Sakib, Hailey Baez, David Paulius +1
The functional object-oriented network (FOON) has been introduced as a knowledge representation, which takes the form of a graph, for symbolic task planning. To get a sequential pl…
Cooking Object's State Identification Without Using Pretrained Model
Md Sadman Sakib
Recently, Robotic Cooking has been a very promising field. To execute a recipe, a robot has to recognize different objects and their states. Contrary to object recognition, state i…
A Gray Box Interpretable Visual Debugging Approach for Deep Sequence Learning Model
Md Mofijul Islam, Amar Debnath, Tahsin Al Sayeed +6
Deep Learning algorithms are often used as black box type learning and they are too complex to understand. The widespread usability of Deep Learning algorithms to solve various mac…