Juan Gómez Ortega

Sensor Fusion for Compliant Robot Motion Control

Force feedback is necessary for accurate force control in robotic manipulators, and thus far, wrist force/torque (F/T) sensors have been used. But an important problem arises when only these types of sensors are used. In a dynamic situation where the manipulator moves in either free or constrained space, the interaction forces and moments at the contact point and also the noncontact ones are measured by the mentioned sensor. In this paper, an estimator based on a sensor fusion strategy integrating the measurements of three different sensors (a wrist F/T sensor, an inertial sensor, and joint sensors) was developed to determine the contact force and torque exerted by the manipulator to its environment. The resulting observer helps to overcome some difficulties of uncertain world models and unknown environments since it reduces the high-frequency and low-frequency spectral contents, i.e., the low-frequency component due to inertia of a heavy tool mass and the high-frequency component due to impacts. The new improvement was experimentally validated in a force/position impedance control loop applied to a Staubli RX60 industrial robotic platform.

Robotic Software Architecture for Multisensor Fusion System

As robotic systems are becoming more complex, distributed, and integrated, there is the need to build sophisticated frameworks to embody intelligence in the robot. This paper presents a component-based software architecture for the integration of industrial robotic platforms with multisensor systems where data fusion is relevant. The architecture is based on an open software robotic platform that is able to fulfill capabilities such as openness, interoperability, adaptability, and modularity, with the addition of hardware in the loop simulator. The resulting robot platform permits easy implementation of model- and sensor-based control concepts, proving to be interesting for robotics research. In addition, it allows the integration of standard industrial components. The entire system has been successfully developed, implemented, and demonstrated for robotic tasks, where multiple and different sensors are required.

Generalized contact force estimator for a robot manipulator

In this work, we present implementation and experiment of the theory of dynamic force sensing for robotic manipulators. In the robot manipulation context, end-effector contact forces may be difficult to measure due to tool interference, yet indirect measurement such as from wrist-mounted force sensors provide force measurement contaminated by inertial forces of the tool distal to the force sensor. In order to extract the contact force exerted by the robot, it is necessary to separate the contact forces from inertial forces. We propose a complete formulation and implementation of a new control strategy based on multi-sensor fusion with three different sensors - that is, encoders mounted at each joint of the robot with six degrees of freedom, a wrist force sensor and accelerometers - whose goal is to obtain a suitable contact force estimator. These new observers contribute to overcome many of the difficulties of uncertain world models and unknown environments, which limit the domain of application of contemporary robots used without external sensory feedback; in addition, the final observer can be applied to any kind of real robot system. An impedance control scheme was proposed to verify the improvement. The experiments were carried out on an industrial Staubli RX60 manipulator with open control system architecture

Sensor fusion of force and acceleration for robot force control

In this paper, robotic sensor fusion of acceleration and force measurement is considered. We discuss the problem of using accelerometers close to the end-effectors of robotic manipulators and how it may improve the force control performance. We introduce a new model-based observer approach to sensor fusion of information from various different sensors. During contact transition, accelerometers and force sensors play a very important role and it can overcome many of the difficulties of uncertain models and unknown environments, which limit the domain of application of currents robots used without external sensory feedback. A model of the robot-grinding tool using the new sensors was obtained by system identification. An impedance control scheme was proposed to verify the improvement The experiments were carried out on an ABB industrial robot with open control system architecture.

Force and Acceleration Sensor Fusion for Compliant Robot Motion Control

In this work, we present implementation and experiment of the theory of dynamic force sensing for robotic manipulators, which uses a sensor fusion technique in order to extract the contact force exerted by the end-effector of the manipulator from those measured by a wrist force sensor, which are corrupted by the inertial forces on the end-effector. We propose a new control strategy based on multisensor fusion with three different sensors— that is, encoders mounted at each joint of the robot with six degrees of freedom, a wrist force sensor and an accelerometer— whose goal is to obtain a suitable contact force estimator for the three Cartesian axes. This new observer contributes to overcome many of the difficulties of uncertain world models and unknown environments, which limit the domain of application of currents robots used without external sensory feedback. An impedance control scheme was proposed to verify the improvement. The experiments were carried out on an ABB industrial robot with open control system architecture.

Automatic Calibration Procedure for a Robotic Manipulator Force Observer

In this paper, we propose a method for self-calibration of a robotic manipulator force observer, which fuses information from force sensors and accelerometers in order to estimate the contact force exerted by a manipulator to its environment, by means of active motion. In robotic operation, during contact transition accelerometers and force sensors play a very important role and serve to overcome many of the difficulties of uncertain world models and unknown environments, limiting the domain of application of current robots used without external sensory provided. The calibration procedure helps to improve the performance as well as enhanced stability and robustness for the transition phase. A variety of accelerometers were used to validate the procedure. A dynamic model of the robot-grinding tool using the new sensors was obtained by system identification. An impedance control scheme was proposed to verify the improvement. The experiments were carried out on an ABB industrial robot with open control system architecture.

Building SCORM embedded WebLabs with LMS interaction

This paper outlines a new procedure for building educational Web Laboratories (WebLabs). These WebLabs are based on JAVA and are offered to learners from Learning Management Systems (LMSs). The Virtual-Remote Laboratories (VRL) are JAVA Applets embedded in Sharable Content Object Reference Model (SCORM) packages that are able to interact with the LMS where they are hosted. This interaction is based on the exchange of information defined by the Run-Time Environment (RTE) and the Run-Time Navigation (RTN) SCORM data models. Both models are managed by the LMS where the SCORM content has been loaded. There are three types of data: read-only, write-only and read/write. In addition, a new JAVA package called scormRTE is presented; it has been developed to facilitate the VRL-LMS information exchange. This package enables a JAVA applet to manipulate directly all the elements of RTN and RTE data models. For the validation, a VRL, created with Easy Java Simulations (EJS), has been developed using this proposal. This VRL has been embedded into a SCORM package in order to build a virtual WebLab about dynamic system modeling. In particular, it is the modelling and identification of a cars suspension dynamics. This WebLab is used in an Industrial Automation course that is offered in several Engineering Grades of the University of Jaén. It is available in the institutional LMS.

Estimación de la Fuerza de Contacto para el Control de Robots Manipuladores con Movimientos Restringidos

Los autores quieren agradecer la subvencion parcial de esta investigacion a traves del proyecto CYCIT DPI2004-04458; del proyecto Autofett GRDI-2000-25135 del Quinto Programa Marco de la union Europea; y del proyecto NAC02.

Sorting Olive Batches for the Milling Process Using Image Processing

The quality of virgin olive oil obtained in the milling process is directly bound to the characteristics of the olives. Hence, the correct classification of the different incoming olive batches is crucial to reach the maximum quality of the oil. The aim of this work is to provide an automatic inspection system, based on computer vision, and to classify automatically different batches of olives entering the milling process. The classification is based on the differentiation between ground and tree olives. For this purpose, three different species have been studied (Picudo, Picual and Hojiblanco). The samples have been obtained by picking the olives directly from the tree or from the ground. The feature vector of the samples has been obtained on the basis of the olive image histograms. Moreover, different image preprocessing has been employed, and two classification techniques have been used: these are discriminant analysis and neural networks. The proposed methodology has been validated successfully, obtaining good classification results.The quality of virgin olive oil obtained in the milling process is directly bound to the characteristics of the olives. Hence, the correct classification of the different incoming olive batches is crucial to reach the maximum quality of the oil. The aim of this work is to provide an automatic inspection system, based on computer vision, and to classify automatically different batches of olives entering the milling process. The classification is based on the differentiation between ground and tree olives. For this purpose, three different species have been studied (Picudo, Picual and Hojiblanco). The samples have been obtained by picking the olives directly from the tree or from the ground. The feature vector of the samples has been obtained on the basis of the olive image histograms. Moreover, different image preprocessing has been employed, and two classification techniques have been used: these are discriminant analysis and neural networks. The proposed methodology has been validated successfully, obtaining good classification results.

Self Calibrating Procedure for a 3D Force Observer

In robotic operations where a manipulator is involved, it is well-known that the quantities measured by a wrist force/torque sensor are corrupted by the dynamics of the end effector and manipulator. To solve this problem, an observer, which fuses information from force sensors and accelerometers, was designed recently in order to estimate the contact force exerted by a manipulator to its environment [1]. This paper introduced a high-speed, high-accuracy, versatile, simple, and fully autonomous technique for the calibration of this robotic manipulator 3D force observer by means of active motion. To verify the improvement, an impedance control scheme was used. A dynamic model of the robot-grinding tool using the new sensors was obtained by system identification. The experiments were carried out on an ABB industrial robot with open control system architecture.