Embedded nonlinear model predictive control for obstacle avoidance using PANOC

Ajay Sathya, Pantelis Sopasakis, Ruben Van Parys, Andreas Themelis, Goele Pipeleers, Panagiotis Patrinos

Research output: Chapter in Book/Report/Conference proceedingConference contribution

11 Citations (Scopus)

Abstract

We employ the proximal averaged Newton-type method for optimal control (PANOC) to solve obstacle avoidance problems in real time. We introduce a novel modeling framework for obstacle avoidance which allows us to easily account for generic, possibly nonconvex, obstacles involving polytopes, ellipsoids, semialgebraic sets and generic sets described by a set of nonlinear inequalities. PANOC is particularly well-suited for embedded applications as it involves simple steps, its implementation comes with a low memory footprint and its fast convergence meets the tight runtime requirements of fast dynamical systems one encounters in modern mechatronics and robotics. The proposed obstacle avoidance scheme is tested on a lab-scale autonomous vehicle.

Original languageEnglish
Title of host publication2018 European Control Conference, ECC 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1523-1528
Number of pages6
ISBN (Electronic)9783952426982
DOIs
Publication statusPublished - Nov 27 2018
Externally publishedYes
Event16th European Control Conference, ECC 2018 - Limassol, Cyprus
Duration: Jun 12 2018Jun 15 2018

Publication series

Name2018 European Control Conference, ECC 2018

Conference

Conference16th European Control Conference, ECC 2018
CountryCyprus
CityLimassol
Period6/12/186/15/18

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Control and Optimization

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