Model Predictive Control for Real-Time Point-to-Point Trajectory Generation

Research output: Contribution to journalArticle


The problem of planning a trajectory for robots starting in an initial state and reaching a final state in a desired interval of time is tackled. We propose an approach based on model predictive control to solve the problem of point-to-point trajectory generation for a given final time. We discuss various choices of models, objective functions, and constraints for generating trajectories to transfer the state of the robot, while respecting physical limitations on the motion as well as fulfilling computational real-time requirements. Extensive simulation results illustrate the use of the approach, and experiments on an industrial robot in a challenging ball-catching task show the effectiveness of the approach also in demanding scenarios with real-time constraints on the computation.


External organisations
  • Italian Institute of Technology
Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Control Engineering


  • Computational modeling, Model predictive control (MPC), Optimization, Planning, real-time control, Real-time systems, Robot sensing systems, robotics, Trajectory, trajectory generation, trajectory optimization.
Original languageEnglish
Pages (from-to)972-983
JournalIEEE Transactions on Automation Science and Engineering
Issue number2
Early online date2018 Dec 24
Publication statusPublished - 2019 Apr 6
Publication categoryResearch

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