LLM | AI LAB @ UniBw Munich

SaynFly @ IEEE ROMAN 2025

Mon, 25 Aug 2025 00:00:00 +0000

At the IEEE International Conference on Robot and Human Interactive Communication (ROMAN) 2025, held in Eindhoven, Netherlands, Björn Döschl presented his latest research titled “SaynFly: An LLM-Modulo Online Planning Framework to Automate UAV Command and Control.” The conference brought together researchers from robotics, human-robot interaction, and automated systems. SaynFly contributes an LLM-modulo online planning framework for UAV command and control, with a particular focus on search and rescue missions.

Conference Details

Conference: IEEE ROMAN 2025

Date: 25 August 2025

Location: Eindhoven University of Technology, De Zaale, 5612 AZ Eindhoven, Netherlands

Summary: Björn Döschl presented his research on SaynFly at IEEE ROMAN 2025.

Paper Abstract

Command and Control (C2) for Unmanned Aerial Vehicle (UAV) missions requires the dynamic coordination of task planning, environmental perception, and navigation strategies. While Large Language Model (LLM-) modulo planning frameworks have shown promise in addressing such complexity, due to their capabilities to understand natural language and common sense, their limited robustness remains a challenge. Recent adaptions of such frameworks made online planning possible, but they do not scale well with the number of actions. This limits the applicability in robotic frameworks with large sets of parameterized actions, such as those encountered in UAV C2. We introduce SaynFly, an LLM-modulo online planning framework that streamlines the action space by discarding infeasible actions using domain-specific knowledge, while leveraging online heuristic search to mitigate reward uncertainty and automate the C2 processes for UAVs. Test results for our Search and Rescue (SAR) validation scenarios show that SaynFly is 70% more efficient compared to existing frameworks while maintaining or exceeding success rates.

LEAP @ CoRL 2024

Sat, 09 Nov 2024 00:00:00 +0000

At the LEAP (Learning Effective Abstractions for Planning) workshop, held as part of the Conference on Robot Learning (CoRL) 2024, Björn Döschl presented his latest research titled “Say-REAPEx: An LLM-Modulo UAV Online Planning Framework for Search and Rescue.” The event brought together leading researchers in planning and robot learning, with a focus on abstraction-based methods. The workshop fostered engaging discussions and offered valuable feedback from peers working at the forefront of AI and robotics.

LEAP @ CoRL 2024

Sat, 09 Nov 2024 00:00:00 +0000

Workshop Details

Event: LEAP Workshop @ CoRL 2024

Date: 9 November 2024

Location: Science Congress Center Munich, Walther-von-Dyck Str. 10, 85748 Munich, Germany

Summary: Björn Döschl presented his research at the LEAP workshop during CoRL 2024.

Event Abstract

The Learning Effective Abstractions for Planning (LEAP) workshop, part of the Conference on Robot Learning (CoRL), took place on 9 November 2024 at the Science Congress Center Munich. Björn Döschl presented his work titled "Say-REAPEx: An LLM-Modulo UAV Online Planning Framework for Search and Rescue" in the form of a poster and gained valuable insights into cutting-edge research in the field of abstractions for robot learning and planning.

Say-REAPEx: An LLM-Modulo UAV Online Planning Framework for Search and Rescue

Fri, 25 Oct 2024 00:00:00 +0000