Probabilistic planning with formal performance guarantees for mobile service robots

Research output: Contribution to journalArticle

Authors

Colleges, School and Institutes

External organisations

  • University of Oxford

Abstract

We present a framework for mobile service robot task planning and execution, based on the use of probabilistic verification techniques for the generation of optimal policies with attached formal performance guarantees. Our approach is based on a Markov decision process model of the robot in its environment, encompassing a topological map where nodes represent relevant locations in the environment, and a range of tasks that can be executed in different locations. The navigation in the topological map is modelled stochastically for a specific time of day. This is done by using spatio-temporal models that provide, for a given time of day, the probability of successfully navigating between two topological nodes, and the expected time to do so. We then present a methodology to generate cost optimal policies for tasks specified in co-safe linear temporal logic. Our key contribution is to address scenarios in which the task may not be achievable with probability one. We formalise a task progression metric and present an approach to generate policies that are formally guaranteed to, in decreasing order of priority: maximise the probability of finishing the task; maximise progress towards completion, if this is not possible; and minimise the expected time or cost required. We illustrate and evaluate our approach with a scalability evaluation in a simulated scenario, and reporting on its implementation in a robot performing service tasks in an office environment for long periods of time.

Details

Original languageEnglish
Pages (from-to)1098–1123
Number of pages26
JournalThe International Journal of Robotics Research
Volume38
Issue number9
Early online date16 Jun 2019
Publication statusPublished - 16 Jun 2019

Keywords

  • Mobile Service Robots, Planning under Uncertainty, Markov Decision Processes, Linear Temporal Logic