6 accepted papers
We present a novel framework that integrates Large Language Models (LLMs) with automated planning and formal verification to streamline the creation and use of Markov Decision Processes (MDP). Our system leverages LLMs to extract structured knowledge in the form of a Prolog knowledge base from natur
We present a novel framework that integrates Large Language Models (LLMs) with automated planning and formal verification to streamline the creation and use of Markov Decision Processes (MDP). Our system leverages LLMs to extract structured knowledge in the form of a Prolog knowledge base from natur…
This work proposes a machine learning approach for the Three-Point Dubins Problem (3PDP) based on classification and regression. The 3PDP is a path planning problem with Dubins curves through 3 waypoints. It is required to find the heading at the intermediate point and the form of the two Dubins pat…
In this work, we propose the Dubins Path Smoothing (DPS) algorithm, a novel and efficient method for smoothing polylines in motion planning tasks. DPS applies to motion planning of vehicles with bounded curvature. In the letter, we show that the generated path: 1) has minimal length, 2) is <inline-f
In this paper, we propose a robot oriented knowledge representation system based on the use of the Prolog language. Our framework hinges on a special organisation of Knowledge Base (KB) that enables: 1) its efficient population from natural language texts using semi-automated procedures based on Lar…
A new solution to the multipoint Markov-Dubins problem via iterative dynamic programming is herein presented. The shortest path problem connecting a sequence of given points in the plane while maintaining angle continuity and bounded curvature is presented. As in the classic two points Dubins proble