The primary goal of this project was to develop a general identification method via software that can be applied to collaborative robots. To achieve this, the collaborative ultralight robots Kinova Gen2 and Kuka LWR4+ with seven degrees of freedom (M-DOF) were used. Specifically, the “recursive Newton-Euler” formulation was used to provide a set of parameters that could describe the body structure and to create a general symbolic representation for collaborative robots. For parameter estimation, the least squares method was used. In addition, trajectories generated with random numbers typically do not produce consistent results; thus, verified trajectories were used. To verify trajectories, real robots were simulated with V-Rep before being executed. When untested trajectories are first tested on robots, undesirable results may occur. This method was convenient for parameter estimation and robot health; saves time; and increases the consistency of results. Algorithms were coded in MATLAB and ROS packages via Python. MATLAB, ROS, and V-Rep worked together in the Ubuntu operating system. The identification methods were modeled, implemented, tested, and validated successfully, and the results for both robots are reported in this article.

The paper considers the convergence problem for a two input affine nonholonomic driftless system with three-dimensional state. The problem is solved using time-invariant static-state feedback and polar transformation which is singular at the origin. The given solution, in general, is local, and the feasible domain is dependent on the properties of the control system. Theoretical considerations are illustrated for the particular system and the results of numerical simulations are presented.