362 research outputs found
Simulation-aided Learning from Demonstration for Robotic LEGO Construction
Recent advancements in manufacturing have a growing demand for fast,
automatic prototyping (i.e. assembly and disassembly) capabilities to meet
users' needs. This paper studies automatic rapid LEGO prototyping, which is
devoted to constructing target LEGO objects that satisfy individual
customization needs and allow users to freely construct their novel designs. A
construction plan is needed in order to automatically construct the
user-specified LEGO design. However, a freely designed LEGO object might not
have an existing construction plan, and generating such a LEGO construction
plan requires a non-trivial effort since it requires accounting for numerous
constraints (e.g. object shape, colors, stability, etc.). In addition,
programming the prototyping skill for the robot requires the users to have
expert programming skills, which makes the task beyond the reach of the general
public. To address the challenges, this paper presents a simulation-aided
learning from demonstration (SaLfD) framework for easily deploying LEGO
prototyping capability to robots. In particular, the user demonstrates
constructing the customized novel LEGO object. The robot extracts the task
information by observing the human operation and generates the construction
plan. A simulation is developed to verify the correctness of the learned
construction plan and the resulting LEGO prototype. The proposed system is
deployed to a FANUC LR-mate 200id/7L robot. Experiments demonstrate that the
proposed SaLfD framework can effectively correct and learn the prototyping
(i.e. assembly and disassembly) tasks from human demonstrations. And the
learned prototyping tasks are realized by the FANUC robot
Robotic Planning under Hierarchical Temporal Logic Specifications
Past research into robotic planning with temporal logic specifications,
notably Linear Temporal Logic (LTL), was largely based on singular formulas for
individual or groups of robots. But with increasing task complexity, LTL
formulas unavoidably grow lengthy, complicating interpretation and
specification generation, and straining the computational capacities of the
planners. In order to maximize the potential of LTL specifications, we
capitalized on the intrinsic structure of tasks and introduced a hierarchical
structure to LTL specifications. In contrast to the "flat" structure, our
hierarchical model has multiple levels of compositional specifications and
offers benefits such as greater syntactic brevity, improved interpretability,
and more efficient planning. To address tasks under this hierarchical temporal
logic structure, we formulated a decomposition-based method. Each specification
is first broken down into a range of temporally interrelated sub-tasks. We
further mine the temporal relations among the sub-tasks of different
specifications within the hierarchy. Subsequently, a Mixed Integer Linear
Program is utilized to generate a spatio-temporal plan for each robot. Our
hierarchical LTL specifications were experimentally applied to domains of
robotic navigation and manipulation. Results from extensive simulation studies
illustrated both the enhanced expressive potential of the hierarchical form and
the efficacy of the proposed method.Comment: 8 pages, 4 figure
A novel algorithm of posture best fit based on key characteristics for large components assembly
Measurement and variation control of geometrical Key Characteristics (KCs), such as flatness and gap of joint faces, coaxiality of cabin sections, is the crucial issue in large components assembly from the aerospace industry. Aiming to control geometrical KCs and to attain the best fit of posture, an optimization algorithm based on KCs for large components assembly is proposed. This approach regards the posture best fit, which is a key activity in Measurement Aided Assembly (MAA), as a two-phase optimal problem. In the first phase, the global measurement coordinate system of digital model and shop floor is unified with minimum error based on singular value decomposition, and the current posture of components being assembly is optimally solved in terms of minimum variation of all reference points. In the second phase, the best posture of the movable component is optimally determined by minimizing multiple KCs' variation with the constraints that every KC respectively conforms to its product specification. The optimal models and the process procedures for these two-phase optimal problems based on Particle Swarm Optimization (PSO) are proposed. In each model, every posture to be calculated is modeled as a 6 dimensional particle (three movement and three rotation parameters). Finally, an example that two cabin sections of satellite mainframe structure are being assembled is selected to verify the effectiveness of the proposed approach, models and algorithms. The experiment result shows the approach is promising and will provide a foundation for further study and application. © 2013 The Authors
One-shot ultraspectral imaging with reconfigurable metasurfaces
One-shot spectral imaging that can obtain spectral information from thousands
of different points in space at one time has always been difficult to achieve.
Its realization makes it possible to get spatial real-time dynamic spectral
information, which is extremely important for both fundamental scientific
research and various practical applications. In this study, a one-shot
ultraspectral imaging device fitting thousands of micro-spectrometers (6336
pixels) on a chip no larger than 0.5 cm, is proposed and demonstrated.
Exotic light modulation is achieved by using a unique reconfigurable
metasurface supercell with 158400 metasurface units, which enables 6336
micro-spectrometers with dynamic image-adaptive performances to simultaneously
guarantee the density of spectral pixels and the quality of spectral
reconstruction. Additionally, by constructing a new algorithm based on
compressive sensing, the snapshot device can reconstruct ultraspectral imaging
information (/~0.001) covering a broad (300-nm-wide)
visible spectrum with an ultra-high center-wavelength accuracy of 0.04-nm
standard deviation and spectral resolution of 0.8 nm. This scheme of
reconfigurable metasurfaces makes the device can be directly extended to almost
any commercial camera with different spectral bands to seamlessly switch the
information between image and spectral image, and will open up a new space for
the application of spectral analysis combining with image recognition and
intellisense
Clinicopathologic features of sporadic inclusion body myositis in China
This study is to investigate the clinical and pathologic features of sporadic inclusion body myositis (sIBM) in China. We retrospectively evaluated the clinical and pathological features of consecutive patients in our department between January 1986 to May 2012. Total 28 cases of sIBM (20 males, 8 females, mean age was 56.93±8.79) were obtained by review of all 4099 muscle biopsy reports. The proportion of sIBM was 0.68% (28/4099) in China. Muscle weakness of quadriceps appeared 100% in 28 cases, while conspicuous atrophy of quadriceps appeared only in five cases (17.86%). Creatase values of 28 patients with sIBM were normal or mildly elevated. Muscle biopsies showed that atrophic fibers resembled more frequent in small angular and irregular shape (82.14%), less common in small round shape (17.86%). Rimmed vacuoles resembled crack (67.86%) and round (32.14%) shape. Mononuclear cell invasion into necrotic muscle fibers (35.71%) was more frequent than non-necrotic muscle fibers (7.14%). sIBM was still a rare disease in China compared to other countries. There were some certain specific pathological characteristics existed in Chinese sIBM patients
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