4 papers
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…
Scout-Assisted Planning for Heterogeneous Robot Teams under Partially Known Environments
Hoang-Dung Bui, Abhish Khanal, Raihan Islam Arnob +1
Autonomous robot teams navigating partially known environments face costly backtracking when ground robots encounter blocked roads that are only revealed upon physical traversal. W…
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…
Learning-Augmented Model-Based Multi-Robot Planning for Time-Critical Search and Inspection Under Uncertainty
Abhish Khanal, Joseph Prince Mathew, Cameron Nowzari +1
In disaster response or surveillance operations, quickly identifying areas needing urgent attention is critical, but deploying response teams to every location is inefficient or of…