Robot and Multibody Dynamics

Robot and Multibody Dynamics: Analysis and Algorithms provides a comprehensive and detailed exposition of a new mathematical approach, referred to as the Spatial Operator Algebra (SOA), for studying the dynamics of articulated multibody systems. The approach is useful in a wide range of applications including robotics, aerospace systems, articulated mechanisms, bio-mechanics and molecular dynamics simulation. The book also: treats algorithms for simulation, including an analysis of complexity of the algorithms, describes one universal, robust, and analytically sound approach to formulating the equations that govern the motion of complex multi-body systems, covers a range of more advanced topics including under-actuated systems, flexible systems, linearization, diagonalized dynamics and space manipulators. Robot and Multibody Dynamics: Analysis and Algorithms will be a valuable resource for researchers and engineers looking for new mathematical approaches to finding engineering solutions in robotics and dynamics.

Uses modern mathematical modeling tools (spatial algebra) and treats algorithms for simulation, including an analysis of complexity of the algorithms Describes one universal, robust, and analytically sound approach to formulating the equations that govern the motion of complex multi-body systems Covers a range of more advanced topics including under-actuated systems, flexible systems, linearization, diagonalized dynamics and space manipulators

Inhalt
Spatial vectors.- Single rigid body dynamics.- Differential kinematics for a serial-chain system.- The mass matrix.- Equations of motion for a serial chain system.- Articulated body models for serial chains.- Operator factorization and inversion of the mass matrix.- Forward dynamics.- Tree topology systems.- The operational space inertia.- Closed chain system dynamics.- Multi-arm manipulators.- Systems with hinge flexibility.- Systems with link flexibility.- Under-actuated systems.- Free-flying space manipulators.- Mass matrix sensitives.- Linearized dynamics models.- Sensitivity of innovations factors.- Diagnolized lagrangian dynamics.- Overview of optimal linear estimation theory.