Theoretically, the operational space control framework can be regarded to be the most advanced control framework for redundant robots. However, in practice, the control performance of this framework is significantly degraded in the presence of model uncertainties and discretizing effects. Using the singular perturbation theory, this paper shows that the same model uncertainties can create different effects on the task space and joint space control performance. From the analysis, a multi-rate operational space control was proposed to minimize the effects of model uncertainties on the control performance and while maintaining the advantages of the original operational space framework. In this paper, we present a stability analysis of the multi-rate operational space control framework using the Lyapunov's direct method.

In this paper, we introduce a new multi-rate hybrid motion and force control using operational space framework. Conventional implementation of operational space control (OSC) does not perform well in the presence of model uncertainties. In order to overcome this issue, a two layered hierarchical controller structure is proposed in this paper. In the outer control loop, the control torque from the OSC is applied to the joint space dynamic model of the robot. By integrating the output of this system, reference joint velocities for the next control loop can be obtained. At the inner control loop, the conventional computed-torque control scheme is used to ensure the robot can track the above desired joint velocities. To illustrate the effectiveness of the proposed controller, intensive experiments have been conducted on the Mitsubishi PA10 7-DOF manipulator. Experimental results indicate that there is a significant improvement in comparison to the conventional implementation and the proposed approach is shown to have performed favorably in comparison to the commercial force controller from PushCorp.

A parallel force and motion control algorithm using observed velocity is presented in this paper. Experimental results show improved control performance in both force and motion subspaces compared with the same controller using filtered velocity.

With our proposed decomposition into layers, a generic framework leading to the reuse of previously produced software and the extraction of useful portions can be achieved. The presented transition function based formalism can be applied to specifying programming frameworks for robot controllers executing very diverse tasks. Formalization introduces rigor into the discussion of the structure of embodied agent controllers. The paper deals with systems consisting of multiple agents executing jobs by: influencing the environment through effectors, gathering information from the environment through sensors and communicating with the other agents through communication channels. A paradigm shift is proposed: from building systems executing jobs, to agents acquiring resources (effectors and receptors) so that they can execute the jobs assigned to them. A supervisory controller coordinates the adequate sequencing of jobs and resolves contentions.

This paper describes an approach based on neural networks (NNs) for geometrical error modeling and compensation for precision motion systems. A laser interferometer is used to obtain the systematic error measurements of the geometrical errors, based on which an error model may be constructed and, consequently, a model-based compensation may be incorporated in the motion-control system. NNs are used to approximate the components of geometrical errors, thus dispensing with the conventional lookup table. Apart from serving as a more adequate model due to its inherent nonlinear characteristics, the use of NNs also results in less memory requirements to implement the error compensation for a specified precision compared to the use of lookup table. The adequacy and clear benefits of the proposed approach are illustrated via applications to various configurations of precision-positioning stages, including a single-axis, a gantry, and a complete XY stage

In this paper, we present a robust observer-based controller (ROC) for robot manipulators to achieve robust velocity estimation and better operational space tracking performance. Without link velocity measurements, the overall ROC system can achieve a semi-global asymptotical stability result for the position and velocity tracking errors, and position and velocity estimation errors. Experimental results using PUMA 560 indicate that the proposed ROC is able to obtain more accurate and less ripple velocity estimation than that obtained from an observer-controller, hence higher tracking performance can be achieved.

This paper addresses the physical dynamic modeling and simulates the adaptive control of a precision gantry stage. The stage is posed as a three-degree-of-freedom system, based on a patented air-bearing stage provided by the Singapore Institute of Manufacturing Technology. Using this stage as the target model, a mathematical model is then built using the Lagrangian equation. An adaptive control method is formulated for the positioning of the stage, with minimal a priori information assumed of the model. A stability analysis is given for the proposed control scheme. Simulation results are also documented to illustrate the feasibility of the scheme. Future direction is to implement the adaptive controller to the actual gantry stage.

An operational space controller that employs a velocity observer and a friction adaptation law to achieve higher tracking accuracy is presented. Without velocity measurements, the overall observer-controller system can achieve a semi-global asymptotic stability for the position and velocity tracking errors, and position and velocity estimation errors. The estimated friction coefficients can also approach the actual coefficients asymptotically. Experimental results indicate that the proposed adaptive observer-controller is able to achieve higher tracking accuracy than the observer-controller without friction compensation.

This paper presents an operational space output feedback controller for non-redundant robot manipulators to achieve trajectory tracking without velocity measurements. The overall system can achieve a semi-global exponential stability (SGES) result for the position, orientation and velocity tracking errors as well as velocity observation errors. Experimental results of the proposed controller indicate good position and orientation tracking performance under parametric uncertainty and payload variations.

The Operational Space Formulation provides a framework for the analysis and control of manipulator systems with respect to the behavior of their end-effectors. Its application to aircraft canopy polishing is shown using a mobile manipulator. The mobile manipulator end-effector maintains a desired force normal to the canopy surface of unknown geometry in doing a compliant polishing motion, while, at the same time, its mobile base moves around the shop floor, effectively increasing the mobile manipulator's workspace. The mobile manipulator consists of a PUMA 560 mounted on top of a Nomad XR4000. Implementation issues are discussed and simultaneous motion and force regulation results are shown.

Robot programming is a very tedious task that involves defining the relevant robot positions and configurations, and writing the robot program to execute the task. In this paper, we present an application of the control of the dynamic behavior of robotic manipulators to achieve walk-through programming of a powered arm. The algorithm is based on impedance control with zero stiffness to allow the robot to be moved by the human hand during walk-through teaching. We demonstrate the application using a welding robot we have customized and improved on for use in shipyards. We describe the architecture, our methodologies, the practical issues and present the results of our performance evaluation.

Presents a navigation algorithm, which integrates a virtual obstacle concept with a potential-field-based method to manoeuvre cylindrical mobile robots in unknown or unstructured environments. This study focuses on the real-time feature of the navigation algorithm for fast moving mobile robots. We mainly consider the potential-field method in conjunction with virtual obstacle concept as the basis of our navigation algorithm. Simulation and experiments of our algorithm shows good performance and ability to overcome the local minimum problem associated with potential field methods.

This paper presents an adaptive partial state feedback controller for rigid-link flexible-joint (RLFJ) robots. The controller compensates for parametric uncertainty throughout the entire mechanical system while only requiring measurement of link position and actuator position. To eliminate the need for measuring link velocity and actuator velocity a set of filters is utilized as a surrogate for the unmeasurable quantities. Based on this set of filters, an adaptive integrator backstepping procedure is used to develop a torque input controller which guarantees semiglobal asymptotic link position tracking while also ensuring that all signals remain bounded during closed-loop operation. Simulation results for a two-link RLFJ robot are utilized to validate the performance of the proposed controller.