A nonlinear disturbance observer for robotic manipulators

A new nonlinear disturbance observer (NDO) for robotic manipulators is derived in this paper. The global exponential stability of the proposed disturbance observer (DO) is guaranteed by selecting design parameters, which depend on the maximum velocity and physical parameters of robotic manipulators. This new observer overcomes the disadvantages of existing DOs, which are designed or analyzed by linear system techniques. It can be applied in robotic manipulators for various purposes such as friction compensation, independent joint control, sensorless torque control and fault diagnosis. The performance of the proposed observer is demonstrated by the friction estimation and compensation for a two-link robotic manipulator. Both simulation and experimental results show the NDO works well

Nonlinear disturbance attenuation control of hydraulic robotics

This paper presents a novel nonlinear disturbance rejection control for hydraulic robots. This method requires two third-order filters as well as inverse dynamics in order to estimate the disturbances. All the parameters for the third-order filters are pre-defined. The proposed method is nonlinear, which does not require the linearization of the rigid body dynamics. The estimated disturbances are used by the nonlinear controller in order to achieve disturbance attenuation. The performance of the proposed approach is compared with existing approaches. Finally, the tracking performance and robustness of the proposed approach is validated extensively on real hardware by performing different tasks under either internal or both internal and external disturbances. The experimental results demonstrate the robustness and superior tracking performance of the proposed approach

Experimental comparison of parameter estimation methods in adaptive robot control

In the literature on adaptive robot control a large variety of parameter estimation methods have been proposed, ranging from tracking-error-driven gradient methods to combined tracking- and prediction-error-driven least-squares type adaptation methods. This paper presents experimental data from a comparative study between these adaptation methods, performed on a two-degrees-of-freedom robot manipulator. Our results show that the prediction error concept is sensitive to unavoidable model uncertainties. We also demonstrate empirically the fast convergence properties of least-squares adaptation relative to gradient approaches. However, in view of the noise sensitivity of the least-squares method, the marginal performance benefits, and the computational burden, we (cautiously) conclude that the tracking-error driven gradient method is preferred for parameter adaptation in robotic applications

Experimental External Force Estimation Using a Non-Linear Observer for 6 axes Flexible-Joint Industrial Manipulators

This paper proposes a non-linear observer to estimate not only the state (position and velocity) of links but also the external forces exerted by the robot during Friction Stir Welding (FSW) processes. The difficulty of performing this process with a robot lies in its lack of rigidity. In order to ensure a better tracking performance, the data such as real positions, velocities of links and external forces are required. However, those variations are not always measured in most industrial robots. Therefore, in this study, an observer is proposed to reconstruct those necessary parameters by using only measurements of motor side. The proposed observer is carried out on a 6 DOF flexible-joint industrial manipulator used in a FSW process.ANR-2010-SEGI-003-01-COROUSSO, French National Agenc

On Sensorless Collision Detection and Measurement of External Forces in Presence of Modeling Inaccuracies

The field of human-robot interaction has garnered significant interest in the last decade. Every form of human-robot coexistence must guarantee the safety of the user. Safety in human-robot interaction is being vigorously studied, in areas such as collision avoidance, soft actuators, light-weight robots, computer vision techniques, soft tissue modeling, collision detection, etc. Despite the safety provisions, unwanted collisions can occur in case of system faults. In such cases, before post-collision strategies are triggered, it is imperative to effectively detect the collisions. Implementation of tactile sensors, vision systems, sonar and Lidar sensors, etc., allows for detection of collisions. However, due to the cost of such methods, more practical approaches are being investigated. A general goal remains to develop methods for fast detection of external contacts using minimal sensory information. Availability of position data and command torques in manipulators permits development of observer-based techniques to measure external forces/torques. The presence of disturbances and inaccuracies in the model of the robot presents challenges in the efficacy of observers in the context of collision detection. The purpose of this thesis is to develop methods that reduce the effects of modeling inaccuracies in external force/torque estimation and increase the efficacy of collision detection. It is comprised of the following four parts: 1. The KUKA Light-Weight Robot IV+ is commonly employed for research purposes. The regressor matrix, minimal inertial parameters and the friction model of this robot are identified and presented in detail. To develop the model, relative weight analysis is employed for identification. 2. Modeling inaccuracies and robot state approximation errors are considered simultaneously to develop model-based time-varying thresholds for collision detection. A metric is formulated to compare trajectories realizing the same task in terms of their collision detection and external force/torque estimation capabilities. A method for determining optimal trajectories with regards to accurate external force/torque estimation is also developed. 3. The effects of velocity on external force/torque estimation errors are studied with and without the use of joint force/torque sensors. Velocity-based thresholds are developed and implemented to improve collision detection. The results are compared with the collision detection module integrated in the KUKA Light-Weight Robot IV+. 4. An alternative joint-by-joint heuristic method is proposed to identify the effects of modeling inaccuracies on external force/torque estimation. Time-varying collision detection thresholds associated with the heuristic method are developed and compared with constant thresholds. In this work, the KUKA Light-Weight Robot IV+ is used for obtaining the experimental results. This robot is controlled via the Fast Research Interface and Visual C++ 2008. The experimental results confirm the efficacy of the proposed methodologies

A passivity approach to controller-observer design for robots

Passivity-based control methods for robots, which achieve the control objective by reshaping the robot system's natural energy via state feedback, have, from a practical point of view, some very attractive properties. However, the poor quality of velocity measurements may significantly deteriorate the control performance of these methods. In this paper the authors propose a design strategy that utilizes the passivity concept in order to develop combined controller-observer systems for robot motion control using position measurements only. To this end, first a desired energy function for the closed-loop system is introduced, and next the controller-observer combination is constructed such that the closed-loop system matches this energy function, whereas damping is included in the controller- observer system to assure asymptotic stability of the closed-loop system. A key point in this design strategy is a fine tuning of the controller and observer structure to each other, which provides solutions to the output-feedback robot control problem that are conceptually simple and easily implementable in industrial robot applications. Experimental tests on a two-DOF manipulator system illustrate that the proposed controller-observer systems enable the achievement of higher performance levels compared to the frequently used practice of numerical position differentiation for obtaining a velocity estimat

Modelling the temperature in joint friction of industrial manipulators

In this paper, a new model for joint dynamic friction of industrial robot manipulators is presented. In particular, the effects of the temperature in the joints are considered. A polynomial-based model is proposed and the parameter estimation is performed without the need of a joint temperature sensor. The use of an observer is then proposed to compensate for the uncertainty in the initial estimation of the temperature value. A large experimental campaign show that the model, in spite of the simplifying assumptions made, is effective in estimating the joint temperature and therefore the friction torque during the robot operations, even for values of velocities that have not been previously employed