On the Complexity Analysis of the Coriolis and Centripetal Effects of a 6 DOF Robot Manipulator

The equations used in calculating the different forces and torques which control the movement of a robot manipulator involve a considerable amount of differential and non-linear terms which possess high computational complexity. Centripetal and Coriolis effects are of great importance when the manipulator is moving at high speeds. The previous effects, based on the Lagrangian formulation, have been simplified and a lower order form produced which has reduced computational complexity. Simulation results for a robot arm have been obtained to check for the validity of the derivation

Identification of Robot Dynamics: A Parallel Processing Approach

Knowledge of the exact characteristics of robot manipulators is one of the most significant factors in designing motion control systems, since the control performance is directly dependant upon the accuracy of the dynamic model. Dynamic models normally have complicated behaviour, including varying inertia depending upon the arm configuration, uncertain load effects, non-linear effects such as the Coriolis and Centripetal forces and interactions among joints. Unless these characteristics are included in the manipulator dynamics exactly, the performance of the controller is not expected to meet the given requirements. This necessitates the development of an efficient method to identify the dynamic parameters of robot arms. This paper will describe the on-line estimation of the link inertial parameters using a semi-customised symbolic representation of the dynamic equations based on the Lagrangian formulation.......

Fast Forward Dynamics Algorithm for Robot Arms Using Multi-Processing

The computation of the direct dynamics problem (forward dynamics) plays a major role in the real-time computer modelling and simulation of robot manipulators. The efficient and computationally inexpensive solution of this problem facilitates the design of real-time robot simulators. In addition, it allows for a better understanding of the key elements affecting robot operations. This work proposes to solve this problem by employing parallel and distributed processing techniques. First, a parallel implementation of a simplified Lagrange-Euler formulation is used to solve for the dynamics. Second, a resulting system of linear equations is solved using Gaussian-Elimination with simple row interchange. Both algorithms are distributed over a multiple-instruction, multiple-data stream (MIMD)computer architecture

The Dynamic Performance of Robot Manipulators Under Different Operating Conditions

The dynamical performance of robot manipulators is greatly affected by the different payloads handled by the end effector (hand). Hence, it is very important, especially for industrial applications, to study the different interconnected relationships between the manipulator joints, speeds, loads and actuation forces. In this paper, a simplified symbolic Lagrangian representation of the different terms presented, with emphasis on the coriolis and centripetal effects. The accuracy and computational efficiency of this new formulation is demonstrated by simulation of a Stanford and PUMA 560 manipulator. Useful quantitative measurements and error analysis are also included on the significance of coriolis and centripetal terms under different load and speed conditions

A Parallel Newton-Euler Formulation for Fast Dynamic Simulation of Robot Manipulators

Advanced control strategies require the inclusion of the dynamical model of the robot arm in the control law. However, the dynamics consist of a highly coupled and non-linear set of equations. Thus, this complexity has always presented a major obstacle in real-time dynamic control applications. The computationally efficient solution of this problem will lead to a better comprehension of the key factors affecting robot operations. This work describes a solution of this problem by employing a parallel processing approach. The dynamics are computed by using a semi-customised Newton-Euler formulation. The algorithm is distributed over a highly-coupled multiple-instruction multiple-data stream (MIMD) computer architecture. The computer system is constructed from general purpose (VLSI) building blocks called (TRANSPUTER. The cost-effectiveness and speed of the scheme is demonstrated by a case study (PUMA 560 robot arm). The communication issues between the different processors are discussed. Speed-up results are included to show the superiority and advantages of the parallel approach

Fast Forward Dynamics Algorithm for Robot Arms Using Multi-Processing

The computation of the direct dynamics problem (forward dynamics) plays a major role in the real-time computer modelling and simulation of robot manipulators. The efficient and computationally inexpensive solution of this problem facilitates the design of real-time robot simulators. In addition, it allows for a better understanding of the key elements affecting robot operations. This work proposes to solve this problem by employing parallel and distributed processing techniques. First, a parallel implementation of a simplified Lagrange-Euler formulation is used to solve for the dynamics. Second, a resulting system of linear equations is solved using Gaussian-Elimination with simple row interchange. Both algorithms are distributed over a multiple-instruction, multiple-data stream (MIMD)computer architecture

Robot Inverse Dynamics Computation Via VLSI Distributed Architects

The computation of the highly coupled dynamic equations has always posed a bottleneck in real-time dynamic control of robot manipulators. Recent advances in VLSI technology make it possible to implement new algorithms that complete these equations and meet real-time constraints. Parallel processing techniques can now be used to reduce the computation time for models of a highly mathematical nature such as the dynamical modelling of robot manipulators. In this work a semi-customised symbolic form of the Lagrange-Euler is divided into subtasks and distributed on a parallel processing system. The development system used consists of an INMOS TRANSPUTER (a VLSI single chip computer) running the OCCAM concurrent programming language. Further, this network is used to introduce parallelism by using different task allocation strategies which flow naturally from the Lagrange-Euler formulation

Distributed VLSI Architectures for Fast Jacobian and Inverse Jacobian Formulations

The rapid development in VLSI technology makes it possible to implement highly complicated and time consuming algorithms to suit real-time applications. Parallel processing techniques can now be used to reduce computational time for models of robot manipulators. The development system used to implement the algorithms consists of an INMOS TRANSPUTER ) a VSLI single-chip computer) running the OCCAM concurrent programming language. This system is used to construct and evaluate the performance and cost effectiveness of several proposed methods to solve for the JACOBIAN and INVERSE JACOBIAN problems with special attention to the case of the robot operating in the neighbourhood of singular points. Detailed analysis is performed and successful results are obtained for a 6 dof robot arm (PUMA 560). Execution time comparisons between Von Neumann (uniprocessing) and parallel processing architectures are also included to show the superiority of the latter approaches