Inertia transfer concept based general method for the determination of the base inertial parameters

Ros, Javier; Plaza, Aitor; Iriarte, Xabier; Aginaga, Jokin

doi:10.1007/s11044-014-9446-3

Cited by 12 publications

(5 citation statements)

References 9 publications

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“…This powerful observation was made originally in (Niemeyer 1990) for floating-base systems with revolute and prismatic joints. It was later independently discovered by for 2D and 3D ) mechanisms, and developed further by Ros et al (2012Ros et al ( , 2015 and Iriarte et al (2013). These papers have provided rules of thumb to characterize minimal parameters for mechanisms with particular joint types.…”

Section: Previous Work On Identifiabilitymentioning

confidence: 90%

Observability in Inertial Parameter Identification

Wensing,

Niemeyer,

Slotine

2017

Preprint

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We present an algorithm to characterize the space of identifiable inertial parameters in system identification of an articulated robot. The algorithm can be applied to general open-chain kinematic trees ranging from industrial manipulators to legged robots. It is the first solution for this case that is provably correct and does not rely on symbolic techniques. The high-level operation of the algorithm is based on a key observation: Undetectable changes in inertial parameters can be interpreted as sequences of inertial transfers across the joints. Drawing on the exponential parameterization of rigid-body kinematics, undetectable inertial transfers are analyzed in terms of linear observability. This analysis can be applied recursively, and lends an overall complexity of O(N ) to characterize parameter identifiability for a system of N bodies. MATLAB source code for the new algorithm is provided.

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Section: Previous Work On Identifiabilitymentioning

confidence: 90%

Observability in Inertial Parameter Identification

Wensing,

Niemeyer,

Slotine

2017

Preprint

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“…There are other symbolic methods that can be applied to reduce even further the complexity of the resulting model: "trigonometricaly simplifiable expression removal" [7], "base parameter formulation of the system inertias" [9,10,11], "base parameter elimination" [6], etc... This methods can be applied directly on top of the presented modeling techniques.…”

Section: Other Symbolic Methodsmentioning

confidence: 99%

Symbolic multibody methods for real-time simulation of railway vehicles

et al. 2017

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In this work, recently developed state-of-the-art symbolic multibody methods are tested to acurately model a complex railway vehicle. The model is generated using a symbolic implementation of the principle of the virtual power. Creep forces are modeled using a direct symbolic implementation of the standard linear Kalker model. No simplifications, as base parameter reduction, partial-linearization or look-up tables for contact kinematics, are used. An Implicit-Explicit integration scheme is proposed to efficiently deal with the stiff creep dynamics. Hard real-time performance is achieved: the CPU time required for a very stable 1 ms integration time step is 256 µs.

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“…M(q(t)) q(t)= M(q(t 0 )) q(t 0 )+ t t 0 (τ + C T (q, q) q − G(q))dt (16) where M(q(t)) q(t) is the generalized momentum at time t. We refer to Eq. ( 16) as "acceleration-free dynamic equations."…”

Section: Two Kinds Of Dynamic Equationsmentioning

confidence: 99%

“…Reference [15] studied the issue of base parameters identification under the condition of noise interference. Reference [16] proposed a base parameters calculation method for general multi-body systems, and ref. [17] studied the base parameters symbolic expressions for planar open-loop and closed-loop mechanisms.…”

Section: Introductionmentioning

confidence: 99%

Modeling and base parameters identification of legged robots

Chang

2021

Robotica

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This paper first uses a decoupling modeling method to model legged robots. The method groups all the degrees of freedom according to the number of limbs, regarding each limb as a manipulator with serial structure, which greatly reduces the number of dynamic parameters that need to be identified simultaneously. On this basis, a step-by-step identification method from the end-effector link to the base link, referred to as “E-B” identification method, is proposed. Simulation verification is carried out on a quadruped robot with 16 degrees of freedom in Gazebo, and the validity of the method proposed is discussed.

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Inertia transfer concept based general method for the determination of the base inertial parameters

Cited by 12 publications

References 9 publications

Observability in Inertial Parameter Identification

Observability in Inertial Parameter Identification

Symbolic multibody methods for real-time simulation of railway vehicles

Modeling and base parameters identification of legged robots

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