A near-singular, flexure jointed, moment sensitive Stewart platform based fore-torque sensor

A force-torque sensor capable of accurate measurement of the three components of externally applied forces and moments is required for force control in robotic applications involving assembly operations. The goal in this paper is to design a Stewart platform based force torque sensor at a near-singular configuration sensitive to externally applied moments. In such a configuration, we show an enhanced mechanical amplification of leg forces and thereby higher sensitivity for the applied external moments. In other directions, the sensitivity will be that of a normal load sensor determined by the sensitivity of the sensing element and the associated electronic amplification, and all the six components of the force and torque can be sensed. In a sensor application, the friction, backlash and other non-linearities at the passive spherical joints of the Stewart platform will affect the measurements in unpredictable ways. In this sensor, we use flexural hinges at the leg interfaces of the base and platform of the sensor. The design dimensions of the flexure joints in the sensor have been arrived at using FEA. The sensor has been fabricated, assembled and instrumented. It has been calibrated for low level loads and is found to show linearity and marked sensitivity to moments about the three orthogonal X, Y and Z axes. This sensor is compatible for usage as a wrist sensor for a robot under development at ISRO Satellite Centre.

Transfer of dynamic learning across postures.

When learning a difficult motor task, we often decompose the task so that the control of individual body segments is practiced in isolation. But on re-composition, the combined movements can result in novel and possibly complex internal forces between the body segments that were not experienced (or did not need to be compensated for) during isolated practice. Here we investigate whether dynamics learned in isolation by one part of the body can be used by other parts of the body to immediately predict and compensate for novel forces between body segments. Subjects reached to targets while holding the handle of a robotic, force-generating manipulandum. One group of subjects was initially exposed to the novel robot dynamics while seated and was then tested in a standing position. A second group was tested in the reverse order: standing then sitting. Both groups adapted their arm dynamics to the novel environment, and this movement learning transferred between seated and standing postures and vice versa. Both groups also generated anticipatory postural adjustments when standing and exposed to the force field for several trials. In the group that had learned the dynamics while seated, the appropriate postural adjustments were observed on the very first reach on standing. These results suggest that the CNS can immediately anticipate the effect of learned movement dynamics on a novel whole-body posture. The results support the existence of separate mappings for posture and movement, which encode similar dynamics but can be adapted independently.

Microfabrication and application of reservoir pins for liquid transfer in biotechnology

Microarraying involves laying down genetic elements onto a solid substrate for DNA analysis on a massively parallel scale. Microarrays are prepared using a pin-based robotic platform to transfer liquid samples from microtitre plates to an array pattern of dots of different liquids on the surface of glass slides where they dry to form spots diameter < 200 μm. This paper presents the design, materials selection, micromachining technology and performance of reservoir pins for microarraying. A conical pin is produced by (i) conventional machining of stainless steel or wet etching of tungsten wire, followed by (ii) micromachining with a focused laser to produce a microreservoir and a capillary channel structure leading from the tip. The pin has a flat end diameter < 100 μm from which a 500 μm long capillary channel < 15 μm wide leads up the pin to a reservoir. Scanning electron micrographs of the metal surface show roughness on the scale of 10 μm, but the pins nevertheless give consistent and reproducible spotting performance. The pin capacity is 80 nanolitres of fluid containing DNA, and at least 50 spots can be printed before replenishing the reservoir. A typical robot holds can hold up to 64 pins. This paper discusses the fabrication technology, the performance and spotting uniformity for reservoir pins, the possible limits to miniaturization of pins using this approach, and the future prospects for contact and non-contact arraying technology.

Image-based localization and pose recovery using scale invariant features

In this paper, we propose a vision based mobile robot localization strategy. Local scale-invariant features are used as natural landmarks in unstructured and unmodified environment. The local characteristics of the features we use prove to be robust to occlusion and outliers. In addition, the invariance of the features to viewpoint change makes them suitable landmarks for mobile robot localization. Scale-invariant features detected in the first exploration are indexed into a location database. Indexing and voting allow efficient recognition of global localization. The localization result is verified by epipolar geometry between the representative view in database and the view to be localized, thus the probability of false localization will be decreased. The localization system can recover the pose of the camera mounted on the robot by essential matrix decomposition. Then the position of the robot can be computed easily. Both calibrated and un-calibrated cases are discussed and relative position estimation based on calibrated camera turns out to be the better choice. Experimental results show that our approach is effective and reliable in the case of illumination changes, similarity transformations and extraneous features. © 2004 IEEE.

Interacción corporal con el ordenador para niños con restricciones motoras

Para los niños el juego es la manera más natural de aprender. Mediante el juego los niños interactúan con su entorno. Cuando se trata de niños con graves restricciones motoras esta interacción se ve limitada. Es por esta razón por la que intentamos poner los medios existentes a su disposición. Este proyecto muestra una interfaz persona-computador para manejar un robot Lego Mindstorm RCX en un entorno virtual proyectado sobre una superficie. En todo momento el sistema es capaz de determinar la posición del robot mediante un sensor Microsoft Kinect. Pretende ser el primer paso en la creación de una interfaz persona-computador para niños con restricciones motoras que ayude en su rehabilitación.

Un entorno de programación multinivel y control modular de robots

En este proyecto final de carrera se van a tratar los aspectos referentes a la ampliación de robots. Para ello se utilizará una placa Arduino que se comunicará con el robot por puerto serie. Esta placa, servirá de plataforma de comunicación entre un PC y el robot, ofreciendo una interfaz del robot anterior con la capacidad de ampliación de la placa Arduino. En el transcurso del proyecto se ha realizado una capa intermedia de código C++ que gestiona el uso de la placa Arduino y del robot iRobot Create a través de la misma. Con objeto de dar también soporte a la programación del robot iRobot Create, se ha elegido un simulador y se le ha dado soporte en la capa anteriormente citada.

Path Planner for Intelligent Laser Surface Modification

An optimal algorithm of manufacturing path planner for intelligent laser surface modification is presented. Elements included in the optimal objective have been analyzed. A 6-D manufacture trace that satisfies the requirements of special craft and 5-axis laser processing robot system has been generated from the path planner by method of parallel section in which combinations of modification spots size with curvature of processing surfaces and modification craft parameters are considered. Related experiments have been successfully carried out with the computer integrated multifunctional laser manufacturing system.

Study of an object recognition algorithm

This project introduces an improvement of the vision capacity of the robot Robotino operating under ROS platform. A method for recognizing object class using binary features has been developed. The proposed method performs a binary classification of the descriptors of each training image to characterize the appearance of the object class. It presents the use of the binary descriptor based on the difference of gray intensity of the pixels in the image. It shows that binary features are suitable to represent object class in spite of the low resolution and the weak information concerning details of the object in the image. It also introduces the use of a boosting method (Adaboost) of feature selection al- lowing to eliminate redundancies and noise in order to improve the performance of the classifier. Finally, a kernel classifier SVM (Support Vector Machine) is trained with the available database and applied for predictions on new images. One possible future work is to establish a visual servo-control that is to say the reac- tion of the robot to the detection of the object.

Visual SLAM using straight lines

The present thesis is focuses on the problem of Simultaneous Localisation and Mapping (SLAM) using only visual data (VSLAM). This means to concurrently estimate the position of a moving camera and to create a consistent map of the environment. Since implementing a whole VSLAM system is out of the scope of a degree thesis, the main aim is to improve an existing visual SLAM system by complementing the commonly used point features with straight line primitives. This enables more accurate localization in environments with few feature points, like corridors. As a foundation for the project, ScaViSLAM by Strasdat et al. is used, which is a state-of-the-art real-time visual SLAM framework. Since it currently only supports Stereo and RGB-D systems, implementing a Monocular approach will be researched as well as an integration of it as a ROS package in order to deploy it on a mobile robot. For the experimental results, the Care-O-bot service robot developed by Fraunhofer IPA will be used.

BertsoBot: lehen urratsak

[EU]Hizkuntzaren prozesamenduko teknikak erabilita, poesia-sorkuntza automatikoan lehen urratsak eman dira. Hau erdiesteko, corpusen prozesamenduan oinarritutako bilaketak erabili dira, bai bilaketa arruntak eta baita bilaketa semantiko aurreratuak ere, horretarako IXA taldean garatutako tresna ezberdinak erabiliaz. Hizkuntza poetikoko testuek, gramatikaltasun eta metrika hertsitik haratago, semantika eta pragmatika barneratuta dituzte. Lan honetan semantikaren auziari heldu zaio nagusiki.

Designing High Performance Factory Automation Applications on Top of DDS

13 p.

Advances towards behaviour-based indoor robotic exploration

215 p.

Mainbot robotaren simulazioa eta nabigazioa

Proiektu honetan IK4-Tekniker fundazioaren Mainbot robotaren simulazioa eta nabigazioa garatu dira. Mainbot robota zentral termosolar baten mantentze-lanetan lagungarria izateko dago pentsatua, eta Ackermann mugimendu-sistema du. Proiektuaren barnean ondorengoak garatu dira: simulazioaren ingurunea, robot simulatua eta nabigazio-sistema. Robota A puntutik B puntura modu autonomoan nabigatzeko gai izan beharko da, eta, horretarako, sentsoreetatik jasotako informazioa erabili beharko du oztopoak ekiditeko.

Pololu 3pi robotaren urrutiko kontrola

Denontzat jakina da, azken urteetan robotikaren munduak zelako garrantzia hartu duen teknologiaren munduan. Hurrengo urteetan badirudi hainbat lanetan giza faktorearen beharra txikiagoa izango dela, roboten erabilera handiagotzen baitoa. Robotak lana modu eraginkor batean egiten du eta horrek bere abantailak ditu, bai produktibitate aldetik, bai alde ekonomikotik. Proiektu honetan Pololu 3pi izeneko robot txiki batekin egin da lan. Nahiz eta robot honek bere mugak badituen, aisialdiko eremuetan pieza garrantzitsua izan daitekela uste da. Robot honek eduki dezakeen ohiko erabilera bat da lurrean marrazturik dagoen labirinto batean ibiltzea marrari jarraituz. Proiektu honetan sistema bat garatu nahi izan da, Pololu 3pi robotaren mugimendua urrutiko aginte batez kontrolatzeko, non erabiltzaileak aukeratu ahal duen zein funtzionalitate nahi duen robota kontrolatzeko: Biraketa Zoroa, Mugitu azeleratuz, Wiimote-a mugituz eta Biraketa normal. Hortaz, proiektuan bi zati uztartzen dira, alde batetik Pololu 3pi robota eta bestetik urrutiko aginte bat, kasu honetan Wii bideokontsolaren Wiimote-a. Programa bat sortu da Pololu 3pi-a Wiimote-arekin mugitu eta kontrolatu ahal izateko. Hori posible izan da Atmega328 izeneko mikrokontrolagailuaren bitartez, berari esker programatu ahal izan baita robotaren programa. Aplikazioak bi zati ditu, alde batetik ikusgai zaigun interfaze grafiko bat, non robotaren funtzionalitate ezberdinak ikusten diren PC-aren pantailan. Bestetik robotak berak duen programa, interfazetik eta Wiimote-tik bidaltzen diren aginduei kasu egiten diena.

Estimation and inference for grasping and manipulation tasks using vision and kinesthetic sensors

This thesis presents a novel framework for state estimation in the context of robotic grasping and manipulation. The overall estimation approach is based on fusing various visual cues for manipulator tracking, namely appearance and feature-based, shape-based, and silhouette-based visual cues. Similarly, a framework is developed to fuse the above visual cues, but also kinesthetic cues such as force-torque and tactile measurements, for in-hand object pose estimation. The cues are extracted from multiple sensor modalities and are fused in a variety of Kalman filters.

A hybrid estimator is developed to estimate both a continuous state (robot and object states) and discrete states, called contact modes, which specify how each finger contacts a particular object surface. A static multiple model estimator is used to compute and maintain this mode probability. The thesis also develops an estimation framework for estimating model parameters associated with object grasping. Dual and joint state-parameter estimation is explored for parameter estimation of a grasped object's mass and center of mass. Experimental results demonstrate simultaneous object localization and center of mass estimation.

Dual-arm estimation is developed for two arm robotic manipulation tasks. Two types of filters are explored; the first is an augmented filter that contains both arms in the state vector while the second runs two filters in parallel, one for each arm. These two frameworks and their performance is compared in a dual-arm task of removing a wheel from a hub.

This thesis also presents a new method for action selection involving touch. This next best touch method selects an available action for interacting with an object that will gain the most information. The algorithm employs information theory to compute an information gain metric that is based on a probabilistic belief suitable for the task. An estimation framework is used to maintain this belief over time. Kinesthetic measurements such as contact and tactile measurements are used to update the state belief after every interactive action. Simulation and experimental results are demonstrated using next best touch for object localization, specifically a door handle on a door. The next best touch theory is extended for model parameter determination. Since many objects within a particular object category share the same rough shape, principle component analysis may be used to parametrize the object mesh models. These parameters can be estimated using the action selection technique that selects the touching action which best both localizes and estimates these parameters. Simulation results are then presented involving localizing and determining a parameter of a screwdriver.

Lastly, the next best touch theory is further extended to model classes. Instead of estimating parameters, object class determination is incorporated into the information gain metric calculation. The best touching action is selected in order to best discern between the possible model classes. Simulation results are presented to validate the theory.