NASA Logo

NTRS

NTRS - NASA Technical Reports Server

Back to Results
Spatially random models, estimation theory, and robot arm dynamicsSpatially random models provide an alternative to the more traditional deterministic models used to describe robot arm dynamics. These alternative models can be used to establish a relationship between the methodologies of estimation theory and robot dynamics. A new class of algorithms for many of the fundamental robotics problems of inverse and forward dynamics, inverse kinematics, etc. can be developed that use computations typical in estimation theory. The algorithms make extensive use of the difference equations of Kalman filtering and Bryson-Frazier smoothing to conduct spatial recursions. The spatially random models are very easy to describe and are based on the assumption that all of the inertial (D'Alembert) forces in the system are represented by a spatially distributed white-noise model. The models can also be used to generate numerically the composite multibody system inertia matrix. This is done without resorting to the more common methods of deterministic modeling involving Lagrangian dynamics, Newton-Euler equations, etc. These methods make substantial use of human knowledge in derivation and minipulation of equations of motion for complex mechanical systems.
Document ID
19890017142
Acquisition Source
Legacy CDMS
Document Type
Conference Paper
Authors
Rodriguez, G.
(California Inst. of Tech. Pasadena, CA, United States)
Date Acquired
September 6, 2013
Publication Date
July 1, 1987
Publication Information
Publication: Jet Propulsion Lab., California Inst. of Tech., Proceedings of the Workshop on Space Telerobotics, Volume 2
Subject Category
Mechanical Engineering
Accession Number
89N26513
Distribution Limits
Public
Copyright
Work of the US Gov. Public Use Permitted.
No Preview Available