A spatial impedance controller for robotic manipulation

Mechanical impedance is the dynamic generalization of stiffness, and determines interactive behavior by definition. Although the argument for explicitly controlling impedance is strong, impedance control has had only a modest impact on robotic manipulator control practice. This is due in part to the fact that it is difficult to select suitable impedances given tasks. A spatial impedance controller is presented that simplifies impedance selection. Impedance is characterized using ¿spatially affine¿ families of compliance and damping, which are characterized by nonspatial and spatial parameters. Nonspatial parameters are selected independently of configuration of the object with which the robot must interact. Spatial parameters depend on object configurations, but transform in an intuitive, well-defined way. Control laws corresponding to these compliance and damping families are derived assuming a commonly used robot model. While the compliance control law was implemented in simulation and on a real robot, this paper emphasizes the underlying theor

Visual attention models for scene text recognition

In this paper we propose an approach to lexicon-free recognition of text in scene images. Our approach relies on a LSTM-based soft visual attention model learned from convolutional features. A set of feature vectors are derived from an intermediate convolutional layer corresponding to different areas of the image. This permits encoding of spatial information into the image representation. In this way, the framework is able to learn how to selectively focus on different parts of the image. At every time step the recognizer emits one character using a weighted combination of the convolutional feature vectors according to the learned attention model. Training can be done end-to-end using only word level annotations. In addition, we show that modifying the beam search algorithm by integrating an explicit language model leads to significantly better recognition results. We validate the performance of our approach on standard SVT and ICDAR'03 scene text datasets, showing state-of-the-art performance in unconstrained text recognition

Developments in impact damage modeling for laminated composite structures

Damage tolerance is the most critical technical issue for composite fuselage structures studied in the Advanced Technology Composite Aircraft Structures (ATCAS) program. The objective here is to understand both the impact damage resistance and residual strength of the laminated composite fuselage structure. An understanding of the different damage mechanisms which occur during an impact event will support the selection of materials and structural configurations used in different fuselage quadrants and guide the development of analysis tools for predicting the residual strength of impacted laminates. Prediction of the damage state along with the knowledge of post-impact response to applied loads will allow for engineered stacking sequencies and structural configurations; intelligent decisions on repair requirements will also result

Coal desulfurization by low temperature chlorinolysis, phase 1

The reported activity covers laboratory scale experiments on twelve bituminous, sub-bituminous and lignite coals, and preliminary design and specifications for bench-scale and mini-pilot plant equipment

Decay of Z into Three Pseudoscalar Bosons

We consider the decay of the $Z$ boson into three pseudoscalar bosons in a general two-Higgs-doublet model. Assuming $m_A$ to be very small, and that of the two physical neutral scalar bosons $h_1$ and $h_2$, $A$ only couples to $Z$ through $h_1$, we find the $Z \to A A A$ branching fraction to be negligible for moderate values of $\tan \beta \equiv v_2/v_1$, if there is no $\lambda_5 (\Phi_1^\dagger \Phi_2)^2 + h.c.$ term in the Higgs potential; otherwise there is no absolute bound but very large quartic couplings (beyond the validity of perturbation theory) are needed for it to be observable.Comment: 8 pages including 1 fi