9 citations · 10 across the 9 of their papers we have counts for
6 papers · 1 filter
Multi-Robot Learning-Informed Task Planning Under Uncertainty
Abhish Khanal, Abhishek Paudel, Hung Pham +1
We want a multi-robot team to complete complex tasks in minimum time where the locations of task-relevant objects are not known. Effective task completion requires reasoning over l…
Object Search in Partially-Known Environments via LLM-informed Model-based Planning and Prompt Selection
Abhishek Paudel, Abhish Khanal, Raihan I. Arnob +2
We present a novel LLM-informed model-based planning framework, and a novel prompt selection method, for object search in partially-known environments. Our approach uses an LLM to…
Effective Task Planning with Missing Objects using Learning-Informed Object Search
Raihan Islam Arnob, Max Merlin, Abhishek Paudel +3
Task planning for mobile robots often assumes full environment knowledge and so popular approaches, like planning via the PDDL, cannot plan when the locations of task-critical obje…
Data-Efficient Policy Selection for Navigation in Partial Maps via Subgoal-Based Abstraction
Abhishek Paudel, Gregory J. Stein
We present a novel approach for fast and reliable policy selection for navigation in partial maps. Leveraging the recent learning-augmented model-based Learning over Subgoals Plann…
Motion Primitives based Path Planning with Rapidly-exploring Random Tree
Abhishek Paudel
We present an approach that generates kinodynamically feasible paths for robots using Rapidly-exploring Random Tree (RRT). We leverage motion primitives as a way to capture the dyn…
Learning for Robot Decision Making under Distribution Shift: A Survey
Abhishek Paudel
With the recent advances in the field of deep learning, learning-based methods are widely being implemented in various robotic systems that help robots understand their environment…