Physics-based Motion Planning with Temporal Logic Specifications

TL;DR

This paper introduces a physics-based motion planning method that integrates Linear Temporal Logic with ontologies for improved autonomous robot task execution, demonstrated through simple mobile robot scenarios.

Contribution

It combines LTL planning with ontologies and physics-based motion planning to enhance robot autonomy in complex, object-manipulation tasks.

Findings

Successfully integrated LTL with ontologies for task reasoning

Enabled physics-based manipulation within temporal logic planning

Demonstrated effectiveness in simple mobile robot scenarios

Abstract

One of the main foci of robotics is nowadays centered in providing a great degree of autonomy to robots. A fundamental step in this direction is to give them the ability to plan in discrete and continuous spaces to find the required motions to complete a complex task. In this line, some recent approaches describe tasks with Linear Temporal Logic (LTL) and reason on discrete actions to guide sampling-based motion planning, with the aim of finding dynamically-feasible motions that satisfy the temporal-logic task specifications. The present paper proposes an LTL planning approach enhanced with the use of ontologies to describe and reason about the task, on the one hand, and that includes physics-based motion planning to allow the purposeful manipulation of objects, on the other hand. The proposal has been implemented and is illustrated with didactic examples with a mobile robot in simple scenarios where some of the goals are occupied with objects that must be removed in order to fulfill the task.