Path Tracking Algorithms for Non-Convex Waiter Motion Problem

Authors

  • Ákos Nagy
    Affiliation

    Department of Automation and Applied Informatics, Faculty of Electrical Engineering and Informatics, Budapest University of Technology and Economics, Hungary

  • Gábor Csorvási
    Affiliation

    Department of Automation and Applied Informatics, Faculty of Electrical Engineering and Informatics, Budapest University of Technology and Economics, Hungary

  • István Vajk
    Affiliation

    Department of Automation and Applied Informatics, Faculty of Electrical Engineering and Informatics, Budapest University of Technology and Economics, Hungary

https://doi.org/10.3311/PPee.11606

Abstract

Originally, motion planning was concerned with problems such as how to move an object from a start to a goal position without hitting anything. Later, it has extended with complications such as kinematics, dynamics, uncertainties, and also with some optimality purpose such as minimum-time, minimum-energy planning. The paper presents a time-optimal approach for robotic manipulators. A special area of motion planning is the waiter motion problem, in which a tablet is moved from one place to another as fastas possible, avoiding the slip of the object that is placed upon it. The presented method uses the direct transcription approach for the waiter problem, which means a optimization problem is formed in order to obtain a time-optimal control for the robot. Problem formulation is extended with a non-convex jerk constraints to avoid unwanted oscillations during the motion. The possible local and global solver approaches for the presented formulation are discussed, and the waiter motion problem is validated by real-life experimental results with a 6-DoF robotic arm.

Keywords:

motion planning, minimum-time control, time-optimal control, convex optimisation, robot control

Published Online

2018-02-07

How to Cite

Nagy, Ákos, Csorvási, G., Vajk, I. “Path Tracking Algorithms for Non-Convex Waiter Motion Problem”, Periodica Polytechnica Electrical Engineering and Computer Science, 62(1), pp. 16–23, 2018. https://doi.org/10.3311/PPee.11606

Issue

Section

Articles