Investigation on the influence of parameter uncertainties in the position tracking of robot manipulators

This paper presents a novel trajectory tracking method for robot arms with uncertainties in parameters. The new controller applies the robust output feedback linearization method and is designed so that it is robust to the variation of parameters. Robustness of the algorithm is evaluated when the parameters of the system are floating over 10 percent up and down. An Unscented Kalman Filter (UKF) is applied for state and parameter estimation purposes. As the considered system has 8 unknown parameters while only 5 of them are independent parameters, UKF is applied only to the augmented system with independent parameters. Three types of simulations are applied depending on sensor groups – first with both position and joint sensors, second with only position sensors and third with only joint sensors. The observation of parameters in these groups is discussed. Simulation results show that when both position sensors and joint sensors are used, all the parameters and states are observable and good tracking performances are obtained. When only position sensors are used, the accuracy of the estimated parameters is reduced, and low tracking performances are revealed. Finally, when only joint sensors are applied, the lengths of robot arms are unobservable, but other parameters related to the dynamic system are observable, and poor tracking performances are given

Power-efficient adaptive behavior through a shape-changing elastic robot

The adaptive morphology of a robot, such as shape adaptation, plays a significant role in adapting its behaviors. Shape adaptation should ideally be achieved without considerable cost, like the power required to deform the robot’s body, and therefore, it is reasonably considered as the last resort in classical rigid robots. However, the last decade has seen an increasing interest in soft robots: robots that can achieve deformability through their inherent material properties or structural compliance. Nevertheless, the dynamics of these types of robots is often complex and therefore it is difficult to substantiate whether the cost like the required power for changing its shape will be worthwhile to achieve the desired behavior. This article presents an approach in the development and analysis of a shape-changing locomoting robot, which relies on the ability of elastic beams to deform and vibrate. Through a proper use of elastic materials and the robot’s vibration-based dynamics, it will be shown both analytically and experimentally how shape adaptation can be designed such that it leads to desirable behaviors, with better power efficiency compared to when the robot solely relies on changing its control input. The results encourage emerging direction in robotics that investigates approaches to change robots’ behaviors through their adaptive morphology. </jats:p

Revising the robust-control design for rigid robot manipulators

Robust controllers for robot manipulators ensure stability of the closed-loop system, even if only partial knowledge of the dynamic model of the manipulator is available. Existing derivations of robust-control laws, while guaranteeing the stability result, present an undesired dependence of the robust-control term on the gains of the controller for the nominal system. This dependence forces larger robust-control terms when the nominal control gains are large. Based on a structured representation of the model uncertainty, this paper proposes a derivation of the robust-control law, where these limitations are removed. Experimental results on the COMAU SMART 3S industrial robot in a 3-degree-of-freedom (DOF) configuration confirm the advantages of the proposed controller