A cloned linguistic decision tree controller for real-time path planning in hostile environments

Oliver D N Turnbull*, Jonathan Lawry, Mark H Lowenberg, Arthur G Richards

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

15 Citations (Scopus)
440 Downloads (Pure)


The idea of a Cloned Controller to approximate optimised control algorithms in a real-time environment is introduced. A Cloned Controller is demonstrated using Linguistic Decision Trees (LDTs) to clone a Model Predictive Controller (MPC) based on Mixed Integer Linear Programming (MILP) for Unmanned Aerial Vehicle (UAV) path planning through a hostile environment. Modifications to the LDT algorithm are proposed to account for attributes with circular domains, such as bearings, and discontinuous output functions. The cloned controller is shown to produce near optimal paths whilst significantly reducing the decision period. Further investigation shows that the cloned controller generalises to the multi-obstacle case although this can lead to situations far outside of the training dataset and consequently result in decisions with a high level of uncertainty. A modification to the algorithm to improve the performance in regions of high uncertainty is proposed and shown to further enhance generalisation. The resulting controller combines the high performance of MPC-MILP with the rapid response of an LDT while providing a degree of transparency/interpretability of the decision making.

Original languageEnglish
Pages (from-to)1-29
Number of pages29
JournalFuzzy Sets and Systems
Early online date28 Aug 2015
Publication statusPublished - 15 Jun 2016


  • Learning
  • Fuzzy control
  • Linguistic modelling
  • Optimization
  • Behavioural cloning
  • Interpretability
  • UAV


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