3 papers
cs.RO2025
Planning with Vision-Language Models and a Use Case in Robot-Assisted Teaching
Xuzhe Dang, Lada KudláÄková, Stefan Edelkamp
Automating the generation of Planning Domain Definition Language (PDDL) with Large Language Model (LLM) opens new research topic in AI planning, particularly for complex real-world…
cs.RO2025
CLIP-Motion: Learning Reward Functions for Robotic Actions Using Consecutive Observations
Xuzhe Dang, Stefan Edelkamp
This paper presents a novel method for learning reward functions for robotic motions by harnessing the power of a CLIP-based model. Traditional reward function design often hinges…
cs.RO2024
SIL-RRT*: Learning Sampling Distribution through Self Imitation Learning
Xuzhe Dang, Stefan Edelkamp
Efficiently finding safe and feasible trajectories for mobile objects is a critical field in robotics and computer science. In this paper, we propose SIL-RRT*, a novel learning-bas…