Abstract
This paper aims to demonstrate a clear relationship between Lagrange equations and Newton-Euler equations regarding computational methods for robot dynamics, from which we derive a systematic method for using either symbolic or on-line numerical computations. Based on the decomposition approach and cross-product operation, a computing method for robot dynamics can be easily developed. The advantages of this computing framework are that: it can be used for both symbolic and on-line numeric computation purposes, and it can also be applied to biped systems, as well as some simple closed-chain robot systems.
Highlights
When looking at robotics research, dynamic modelling is basically a form of artwork
The biped robot is the target of a complex dynamic system study [1] that reveals a demand for a computer‐aided systematic derivation tools for robotics
Tošic [2] proposed the benefits of a symbolic simulation of an engineering system, while Cetinkunt [3] proposed a symbolic modelling of the dynamics of robotic manipulators on the numerical tool REDUCE
Summary
When looking at robotics research, dynamic modelling is basically a form of artwork. The complexity of a dynamic model concerns the degrees of freedom (DOFs) of a machine or a robot and the dynamic model of a low DOFs robot can be developed, but dynamic models for a high DOFs robot are difficult to derive by hand. D9u, c4t8-B:2a0s1ed Method for Computing the Dynamic Equation of Robots engineering education [5], providing the steps for determining a system dynamics model, but it does not support online simulations that integrate both system models and control rules Numerous contributions in both algorithms and their computational efficiency have been made in the field of robot dynamics [6,7,8,9]. Based on the decomposition approach and cross‐product operation, a computing framework can be developed to calculate the inertia matrix, the Coriolis and centrifugal matrix, and the gravity force vector of robot dynamics equations The advantages of this computing method are that: it can be used for both symbolic and the on‐line numeric computation purposes, and it can be applied to a closed‐chain robot system. We present several robotic system examples to demonstrate the versatility of the proposed method
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