Suppress vibration on robotic polishing with impedance matching

Installing force-controlled end-effectors on the end of industrial robots has become the mainstream method for robot force control. Additionally, during the polishing process, contact force stability has an important impact on polishing quality. However, due to the difference between the robot structure and the force-controlled end-effector, in the polishing operation, direct force control will have impact during the transition from noncontact to contact between the tool and the workpiece. Although impedance control can solve this problem, industrial robots still produce vibrations with high inertia and low stiffness. Therefore, this research proposes an impedance matching control strategy based on traditional direct force control and impedance control methods to improve this problem. This method's primary purpose is to avoid force vibration in the contact phase and maintain force-tracking performance during the dynamic tracking phase. Simulation and experimental results show that this method can smoothly track the contact force and reduce vibration compared with traditional force control and impedance control

Force Tracking Impedance Control with Unknown Environment at the Microscale.

International audienceA new method to estimate the environment parameters is proposed in order to perform force tracking in impedance control despite the presence of an unknown environment. In impedance force tracking, the location of the environment relative to the robot and the stiffness of the environment should be known. The proposed method estimates the environment location and stiffness using only force and position measurements. The study is done for microscale taking into consideration microscale specificities, especially pull-off force. The impedance control formulation is tested experimentally in a contact transition scenario consisting of a compliant microforce sensor mounted on a microrobotic positioner, and three compliant microstructures with different stiffness. A traditional double mass-spring-damper model of the overall robot is employed to develop the closed-loop impedance control

SMC framework in motion control systems

Design of a motion control system should take into account both the unconstrained motion performed without interaction with environment or other system, and the constrained motion where system is in contact with environment or has certain functional interaction with another system. In this paper control systems design approach, based on siding mode methods, that allows selection of control for generic tasks as trajectory and/or force tracking as well as for systems that require maintain some functional relation like bilateral or multilateral systems, establisment of virtual relation among mobile robots or control of haptic systems is presented. It is shown that all basic motion control problems - trajectory tracking, force control, hybrid position/force control scheme and the impedance control - can be treated in the same way while avoiding the structural change of the controller and guarantying stable behavior of the system In order to show applicability of the proposed techniques simulation and experimental results for high precision systems in microsystems assembly tasks and bilateral control systems are presente

Control of interconnected mechanical systems

In this paper control systems design approach, based on siding mode methods, that allows maintain some functional relation – like bilateral or multilateral systems, establishment of virtual relation among mobile robots or control of haptic systems - is presented. It is shown that all basic motion control problems - trajectory tracking, force control, hybrid position/force control scheme and the impedance control for the interacting systems- can be treated in the same way while avoiding the structural change of the controller and guarantying stable behavior of the system In order to show applicability of the proposed techniques simulation and experimental results for high precision systems in microsystems assembly tasks are presented.

Cooperative Object Manipulation with Force Tracking on the da Vinci Research Kit

The da Vinci Surgical System is one of the most established robot-assisted surgery device commended for its dexterity and ergonomics in minimally invasive surgery. Conversely, it inherits disadvantages which are lack of autonomy and haptic feedback. In order to address these issues, this work proposes an industry-inspired solution to the field of force control in medical robotics. This approach contributes to shared autonomy by developing a controller for cooperative object manipulation with force tracking utilizing available manipulators and force feedback. To achieve simultaneous position and force tracking of the object, master and slave manipulators were assigned then controlled with Cartesian position control and impedance control respectively. Because impedance control requires a model-based feedforward compensation, we identified the lumped base parameters of mass, inertias, and frictions of a three degree-of-freedom double four-bar linkage mechanism with least squares and weighted least squares regression methods. Additionally, semidefinite programming was used to constrain the parameters to a feasible physical solution in standard parameter space. Robust stick-slip static friction compensation was applied where linear Viscous and Coulomb friction was inadequate in modeling the prismatic third joint. The Robot Operating System based controller was tested in RViz to check the cooperative kinematics of up to three manipulators. Additionally, simulation with the dynamic engine Gazebo verified the cooperative controller applying a constant tension force on a massless spring-damper virtual object. With adequate model feedback linearization, the cooperative impedance controller tested on the da Vinci Research Kit yielded stable tension force tracking while simultaneously moving in Cartesian space. The maximum force tracking error was +/- 0.5 N for both a compliant and stiff manipulated object

Iterative Machine Learning for Precision Trajectory Tracking with Series Elastic Actuators

When robots operate in unknown environments small errors in postions can lead to large variations in the contact forces, especially with typical high-impedance designs. This can potentially damage the surroundings and/or the robot. Series elastic actuators (SEAs) are a popular way to reduce the output impedance of a robotic arm to improve control authority over the force exerted on the environment. However this increased control over forces with lower impedance comes at the cost of lower positioning precision and bandwidth. This article examines the use of an iteratively-learned feedforward command to improve position tracking when using SEAs. Over each iteration, the output responses of the system to the quantized inputs are used to estimate a linearized local system models. These estimated models are obtained using a complex-valued Gaussian Process Regression (cGPR) technique and then, used to generate a new feedforward input command based on the previous iteration's error. This article illustrates this iterative machine learning (IML) technique for a two degree of freedom (2-DOF) robotic arm, and demonstrates successful convergence of the IML approach to reduce the tracking error.Comment: 9 pages, 16 figure. Submitted to AMC Worksho

Adaptive impedance control of robot manipulators based on Q-learning and disturbance observer

In this paper, an adaptive impedance control combined with disturbance observer (DOB) is developed for a general class of uncertain robot manipulators in discrete time. The impedance control is applied to realize the interaction force control of robot manipulators in unknown, time-varying environments. The optimal reference trajectory is produced by impedance control, and the impedance parameters are achieved using Q-learning technique, which is implemented based on trajectory tracking errors. The position control with DOB of robot manipulators is implemented to track the virtual desired trajectory, and the DOB is designed to compensate for unknown compounded disturbance function by bounding both tracking error inputs and compounded disturbance inputs in a permitted control region, of which the compounded disturbance function is taken into account of all uncertain terms and external disturbances. The appropriate DOB parameters are selected applying linear matrix inequalities (LMIs) method. Both the impedance control and the bounded DOB control can well guarantee semiglobal uniform boundness of the closed-loop robot systems based on Lyapunov analysis and Schur complement theory. Simulation results are performed to test and verify effectiveness of the investigated combining adaptive impedance control with DOB

Optimal critic learning for robot control in time-varying environments

In this paper, optimal critic learning is developed for robot control in a time-varying environment. The unknown environment is described as a linear system with time-varying parameters, and impedance control is employed for the interaction control. Desired impedance parameters are obtained in the sense of an optimal realization of the composite of trajectory tracking and force regulation. Q-function based critic learning is developed to determine the optimal impedance parameters without the knowledge of the system dynamics. Simulation results are presented and compared with existing methods, and the efficacy of the proposed method is verified