On dynamically consistent Jacobian inverse for non-holonomic robotic systems

• Autorzy: Ratajczak J. , Tchoń K.

Identyfikatory

DOI

10.1515/acsc-2017-0033

• Języki publikacji: EN

Abstrakty

EN

This paper presents the dynamically consistent Jacobian inverse for non-holonomic robotic system, and its application to solving the motion planning problem. The system’s kinematics are represented by a driftless control system, and defined in terms of its input-output map in accordance with the endogenous configuration space approach. The dynamically consistent Jacobian inverse (DCJI) has been introduced by means of a Riemannian metric in the endogenous configuration space, exploiting the reduced inertia matrix of the system’s dynamics. The consistency condition is formulated as the commutativity property of a diagram of maps. Singular configurations of DCJI are studied, and shown to coincide with the kinematic singularities. A parametric form of DCJI is derived, and used for solving example motion planning problems for the trident snake mobile robot. Some advantages in performance of DCJI in comparison to the Jacobian pseudoinverse are discovered.

Słowa kluczowe

EN

non-holonomic system; motion; Jacobian inverse; dynamic consistency; metric; motion planning

• Wydawca: Polish Academy of Sciences, Committee of Automatic Control and Robotics
• Czasopismo: Archives of Control Sciences
• Rocznik: 2017
• Tom: Vol. 27, no. 4
• Strony: 555--573
• Opis fizyczny: Bibliogr. 23 poz., tab., wykr., wzory

Twórcy

autor

Ratajczak J.

• Department of Cybernetics and Robotics, Wrocław University of Science and Technology, ul. Janiszewskiego 11/17, 50-372 Wrocław, Poland

autor

Tchoń K.

• Department of Cybernetics and Robotics, Wrocław University of Science and Technology, ul. Janiszewskiego 11/17, 50-372 Wrocław, Poland

Bibliografia

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Uwagi

EN

This research was supported by the Wrocław University of Science and Technology under a statutory research project.

PL

Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017).