3D Visual Data-Driven Spatiotemporal Deformations for Non-Rigid Object Grasping Using Robot Hands

Sensing techniques are important for solving problems of uncertainty inherent to intelligent grasping tasks. The main goal here is to present a visual sensing system based on range imaging technology for robot manipulation of non-rigid objects. Our proposal provides a suitable visual perception system of complex grasping tasks to support a robot controller when other sensor systems, such as tactile and force, are not able to obtain useful data relevant to the grasping manipulation task. In particular, a new visual approach based on RGBD data was implemented to help a robot controller carry out intelligent manipulation tasks with flexible objects. The proposed method supervises the interaction between the grasped object and the robot hand in order to avoid poor contact between the fingertips and an object when there is neither force nor pressure data. This new approach is also used to measure changes to the shape of an object’s surfaces and so allows us to find deformations caused by inappropriate pressure being applied by the hand’s fingers. Test was carried out for grasping tasks involving several flexible household objects with a multi-fingered robot hand working in real time. Our approach generates pulses from the deformation detection method and sends an event message to the robot controller when surface deformation is detected. In comparison with other methods, the obtained results reveal that our visual pipeline does not use deformations models of objects and materials, as well as the approach works well both planar and 3D household objects in real time. In addition, our method does not depend on the pose of the robot hand because the location of the reference system is computed from a recognition process of a pattern located place at the robot forearm. The presented experiments demonstrate that the proposed method accomplishes a good monitoring of grasping task with several objects and different grasping configurations in indoor environments.

Topological SLAM using a graph-matching based method on omnidirectional images

Comunicación presentada en el XI Workshop of Physical Agents, Valencia, 9-10 septiembre 2010.

Construction of Intelligent Virtual Worlds Using a Grammatical Framework

The potential of integrating multiagent systems and virtual environments has not been exploited to its whole extent. This paper proposes a model based on grammars, called Minerva, to construct complex virtual environments that integrate the features of agents. A virtual world is described as a set of dynamic and static elements. The static part is represented by a sequence of primitives and transformations and the dynamic elements by a series of agents. Agent activation and communication is achieved using events, created by the so-called event generators. The grammar defines a descriptive language with a simple syntax and a semantics, defined by functions. The semantics functions allow the scene to be displayed in a graphics device, and the description of the activities of the agents, including artificial intelligence algorithms and reactions to physical phenomena. To illustrate the use of Minerva, a practical example is presented: a simple robot simulator that considers the basic features of a typical robot. The result is a functional simple simulator. Minerva is a reusable, integral, and generic system, which can be easily scaled, adapted, and improved. The description of the virtual scene is independent from its representation and the elements that it interacts with.

VdBH 222: a starburst cluster in the inner Milky Way

Context. It has been suggested that the compact open cluster VdBH 222 is a young massive distant object. Aims. We set out to characterise VdBH 222 using a comprehensive set of multi-wavelength observations. Methods. We obtained multi-band optical (UBVR) and near-infrared (JHKS) photometry of the cluster field, as well as multi-object and long-slit optical spectroscopy for a large sample of stars in the field. We applied classical photometric analysis, as well as more sophisticated methods using the CHORIZOS code, to determine the reddening to the cluster. We then plotted dereddened HR diagrams and determined cluster parameters via isochrone fitting. Results. We have identified a large population of luminous supergiants confirmed as cluster members via radial velocity measurements. We find nine red supergiants (plus one other candidate) and two yellow supergiants. We also identify a large population of OB stars. Ten of them are bright enough to be blue supergiants. The cluster lies behind ≈7.5 mag of extinction for the preferred value of RV = 2.9. Isochrone fitting allows for a narrow range of ages between 12 and 16 Ma. The cluster radial velocity is compatible with distances of ~6 and ~10 kpc. The shorter distance is inconsistent with the age range and Galactic structure. The longer distance implies an age ≈ 12 Ma and a location not far from the position where some Galactic models place the far end of the Galactic bar. Conclusions. VdBH 222 is a young massive cluster with a likely mass >20 000 M⊙. Its population of massive evolved stars is comparable to that of large associations, such as Per OB1. Its location in the inner Galaxy, presumably close to the end of the Galactic bar, adds to the increasing evidence for vigorous star formation in the inner regions of the Milky Way.

Active Visual Features Based on Events to Guide Robot Manipulators in Tracking Tasks

Traditional visual servoing systems do not deal with the topic of moving objects tracking. When these systems are employed to track a moving object, depending on the object velocity, visual features can go out of the image, causing the fail of the tracking task. This occurs specially when the object and the robot are both stopped and then the object starts the movement. In this work, we have employed a retina camera based on Address Event Representation (AER) in order to use events as input in the visual servoing system. The events launched by the camera indicate a pixel movement. Event visual information is processed only at the moment it occurs, reducing the response time of visual servoing systems when they are used to track moving objects.