Efficient robot dynamics for high sampling rate motions: case studies and benchmarks

The implementation of on-line algorithms for robot dynamics is made difficult by the complex nature of the equations. However, most of the advanced control techniques, especially model-based algorithms, require the inclusion of the dynamic model in the ‘control-law’. In this case, the dynamics are computed at each sampling instant. Hence, the development of simplified and computationally viable dynamic models is crucial for the enhancement of controller design. These models should satisfy two criteria. First, the simplification of the model should not lead to loss of accuracy which will destabilize the robot performance. Second, the model must meet real-time constraints and help to achieve high sampling rate motions. In this paper, a simplified formulation of robot dynamics based on the Lagrange-Euler is introduced. However, the work emphasizes the computational efficiency of this technique as compared to some existing ones. The advantage of the proposed technique emanates from its simple and well-defined...

[1]  Hironori Kasahara,et al.  Parallel processing of robot-arm control computation on a multimicroprocessor system , 1985, IEEE J. Robotics Autom..

[2]  C. G. Lee,et al.  Development of the generalized d'Alembert equations of motion for mechanical manipulators , 1983, The 22nd IEEE Conference on Decision and Control.

[3]  Yuan F. Zheng,et al.  Computation of Multibody System Dynamics by a Multiprocessor Scheme , 1986, IEEE Transactions on Systems, Man, and Cybernetics.

[4]  C. S. George Lee,et al.  Efficient Parallel Algorithm for Robot Inverse Dynamics Computation , 1986, IEEE Transactions on Systems, Man, and Cybernetics.

[5]  Vassilios D. Tourassis Principles and design of model-based robot controllers , 1988 .

[6]  H Faessler,et al.  Computer-Assisted Generation of Dynamical Equations for Multibody Systems , 1986 .

[7]  Trevor Mudge,et al.  Connection between formulations of robot arm dynamics with applications to simulation and control , 1981 .

[8]  A. Bejczy Robot arm dynamics and control , 1974 .

[9]  James H. Herzog,et al.  Distributed Computer Architecture and Fast Parallel Algorithms in Real-Time Robot Control , 1986, IEEE Transactions on Systems, Man, and Cybernetics.

[10]  Karl Johan Åström,et al.  Adaptive Control , 1989, Embedded Digital Control with Microcontrollers.

[11]  John M. Hollerbach,et al.  A Recursive Lagrangian Formulation of Maniputator Dynamics and a Comparative Study of Dynamics Formulation Complexity , 1980, IEEE Transactions on Systems, Man, and Cybernetics.

[12]  Neil M. Swartz Arm Dynamics Simulation , 2007, J. Field Robotics.

[13]  Miomir Vukobratovic,et al.  An Approach to Parallel Processing of Dynamic Robot Models , 1988, Int. J. Robotics Res..

[14]  C. S. George Lee,et al.  Efficient parallel algorithms for robot forward dynamics computation , 1988, IEEE Trans. Syst. Man Cybern..

[15]  Matthew T. Mason,et al.  Robot Motion: Planning and Control , 1983 .

[16]  J. Denavit,et al.  A kinematic notation for lower pair mechanisms based on matrices , 1955 .

[17]  S. Shankar Sastry,et al.  Adaptive Control of Mechanical Manipulators , 1987, Proceedings. 1986 IEEE International Conference on Robotics and Automation.

[18]  Albert Y. Zomaya,et al.  Transputer Networks for the Dynamic Simulation of Robot Manipulators , 1992, Int. J. Comput. Simul..

[19]  William M. Silver On the Equivalence of Lagrangian and Newton-Euler Dynamics for Manipulators , 1982 .

[20]  R. Paul Robot manipulators : mathematics, programming, and control : the computer control of robot manipulators , 1981 .

[21]  J. Y. S. Luh,et al.  On-Line Computational Scheme for Mechanical Manipulators , 1980 .

[22]  Pradeep K. Khosla,et al.  Choosing sampling rates for robot control , 1987, Proceedings. 1987 IEEE International Conference on Robotics and Automation.

[23]  M. C. Leu,et al.  Computer generation of robot dynamics equations and the related issues , 1986, J. Field Robotics.

[24]  R. A. Lewis,et al.  Autonomous manipulation on a robot: Summary of manipulator software functions , 1974 .

[25]  C. L. Philip Chen,et al.  Efficient scheduling algorithms for robot inverse dynamics computation on a multiprocessor system , 1988, IEEE Trans. Syst. Man Cybern..

[26]  John J. Craig,et al.  Introduction to Robotics Mechanics and Control , 1986 .

[27]  John J. Murray,et al.  Customized computational robot dynamics , 1987, J. Field Robotics.

[28]  John J. Murray,et al.  Computational robot dynamics: Foundations and applications , 1985, J. Field Robotics.

[29]  Albert Y. Zomaya,et al.  Dynamic performance of robot manipulators under different operating conditions , 1990 .

[30]  B. J. Torby,et al.  Advanced dynamics for engineers , 1984 .

[31]  Robert J. Schilling,et al.  Fundamentals of robotics - analysis and control , 1990 .

[32]  Mark W. Spong,et al.  Robot dynamics and control , 1989 .

[33]  Richard H. Lathrop,et al.  Parallelism in Manipulator Dynamics , 1985 .

[34]  Thomas R. Kane,et al.  The Use of Kane's Dynamical Equations in Robotics , 1983 .

[35]  Roy Featherstone,et al.  Robot Dynamics Algorithms , 1987 .

[36]  David E. Orin,et al.  Efficient Dynamic Computer Simulation of Robotic Mechanisms , 1982 .

[37]  Charles P. Neuman,et al.  Properties and structure of dynamic robot models for control engineering applications , 1985 .

[38]  J. Murray,et al.  ARM: An algebraic robot dynamic modeling program , 1984, ICRA.

[39]  M. H. Raibert,et al.  Manipulator control using the configuration space method , 1978 .

[40]  J. Y. S. LUH,et al.  Scheduling of Parallel Computation for a Computer-Controlled Mechanical Manipulator , 1982, IEEE Transactions on Systems, Man, and Cybernetics.