12,013 research outputs found

    A gravitational-wave probe of effective quantum gravity

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    The Green-Schwarz anomaly-cancelling mechanism in string theories requires a Chern-Simons term in the Einstein-Hilbert action, which leads to an amplitude birefringence of spacetime for the propagation of gravitational waves. While the degree of birefringence may be intrinsically small, its effects on a gravitational wave will accumulate as the wave propagates. The proposed Laser Interferometer Space Antenna (LISA) will be sensitive enough to observe the gravitational waves from sources at cosmological distances great enough that interesting bounds on the Chern-Simons may be found. Here we evaluate the effect of a Chern-Simons induced spacetime birefringence to the propagation of gravitational waves from such systems. We find that gravitational waves from in coalescing binary black hole system are imprinted with a signature of Chern-Simons gravity. This signature appears as a time-dependent change in the apparent orientation of the binary's orbital angular momentum with respect to the observer line-of-sight, with the change magnitude reflecting the integrated history of the Chern-Simons coupling over the worldline of a radiation wavefront. While spin-orbit coupling in the binary system will also lead to an evolution of the system's orbital angular momentum, the time dependence and other details of this \emph{real} effect are different than the \emph{apparent} effect produced by Chern-Simons birefringence, allowing the two effects to be separately identified.Comment: 14 pages, no figures, submitted to Phys. Rev.

    Tracking in Urban Traffic Scenes from Background Subtraction and Object Detection

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    In this paper, we propose to combine detections from background subtraction and from a multiclass object detector for multiple object tracking (MOT) in urban traffic scenes. These objects are associated across frames using spatial, colour and class label information, and trajectory prediction is evaluated to yield the final MOT outputs. The proposed method was tested on the Urban tracker dataset and shows competitive performances compared to state-of-the-art approaches. Results show that the integration of different detection inputs remains a challenging task that greatly affects the MOT performance

    Extrapolation of Airborne Polarimetric and Interferometric SAR Data for Validation of Bio-Geo-Retrieval Algorithms for Future Spaceborne SAR Missions

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    Spaceborne SAR system concepts and mission design is often based on algorithms developed and the experience gathered from airborne SAR experiments and associated dedicated campaigns. However, airborne SAR systems have better performance parameters than their future space-borne counterparts as their design is not impacted by mass, power, and storage constraints. This paper describes a methodology to extrapolate spaceborne quality SAR image products from long wavelength airborne polarimetric SAR data which were acquired especially for the development and validation of bio/geo-retrieval algorithms in forested regions. For this purpose not only system (sensor) related parameters are altered, but also those relating to the propagation path (ionosphere) and to temporal decorrelation

    Optimal Schedules in Multitask Motor Learning

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    Although scheduling multiple tasks in motor learning to maximize long-term retention of performance is of great practical importance in sports training and motor rehabilitation after brain injury, it is unclear how to do so. We propose here a novel theoretical approach that uses optimal control theory and computational models of motor adaptation to determine schedules that maximize long-term retention predictively. Using Pontryagin’s maximum principle, we derived a control law that determines the trial-by-trial task choice that maximizes overall delayed retention for all tasks, as predicted by the state-space model. Simulations of a single session of adaptation with two tasks show that when task interference is high, there exists a threshold in relative task difficulty below which the alternating schedule is optimal. Only for large differences in task difficulties do optimal schedules assign more trials to the harder task. However, over the parameter range tested, alternating schedules yield long-term retention performance that is only slightly inferior to performance given by the true optimal schedules. Our results thus predict that in a large number of learning situations wherein tasks interfere, intermixing tasks with an equal number of trials is an effective strategy in enhancing long-term retention

    Meteoroid Impact Detection for Exploration of Asteroids (MIDEA)

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    Asteroids contain a wealth of resources including water and precious metals that can be extracted. These resources could be applied to in-space manufacture of products that depend less on material launched from Earth's surface. The Meteoroid Impact Detection for Exploration of Asteroids (MIDEA) concept addresses the challenge of characterizing an asteroid surface using a small satellite with a constellation of free-flying plasma sensors to assess the asteroids viability for in situ resource utilization (ISRU). The plasma sensors detect ions ejected from the surface of an asteroid by meteoroid impacts, enabling the surface composition to be inferred. The objective of this NIAC Phase I study was to demonstrate feasibility of the MIDEA architecture in the context of proximity operations around an asteroid target and to develop the design of an orbital geometry and attitude control strategy for the ultralight plasma sensors. This was undertaken through a simulation framework to identify and characterize a favorable orbit for the MIDEA sensor constellation, and developing a sensor geometry that is consistent with maintaining the pointing requirements necessary to operate with sufficient power generation. Our study showed that a polar orbit aligned along the asteroid terminator provided sufficient stability for the sensors in the low gravitational environment under the influence of substantial solar radiation pressure. Reflector vanes using controlled reflectivity devices implemented with liquid crystal technology are capable of maintaining the sensor attitude so that it consistently points its solar panels in the sun direction and the sensor electrode at the asteroid surface. Finally, the reduction in meteoroid impact detection due to visibility constraints from the proposed orbit does not substantially extend the expected mission duration. These results indicate that the MIDEA concept can be achievable using a 1020 kg spacecraft, which would be able to characterize the surface composition of an asteroid within 3050 days of proximity operations. This architecture, implemented in parallel to multiple asteroid targets, would enable widespread exploration of near-Earth asteroids at low cost

    Synthetic data enables faster annotation and robust segmentation for multi-object grasping in clutter

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    Object recognition and object pose estimation in robotic grasping continue to be significant challenges, since building a labelled dataset can be time consuming and financially costly in terms of data collection and annotation. In this work, we propose a synthetic data generation method that minimizes human intervention and makes downstream image segmentation algorithms more robust by combining a generated synthetic dataset with a smaller real-world dataset (hybrid dataset). Annotation experiments show that the proposed synthetic scene generation can diminish labelling time dramatically. RGB image segmentation is trained with hybrid dataset and combined with depth information to produce pixel-to-point correspondence of individual segmented objects. The object to grasp is then determined by the confidence score of the segmentation algorithm. Pick-and-place experiments demonstrate that segmentation trained on our hybrid dataset (98.9%, 70%) outperforms the real dataset and a publicly available dataset by (6.7%, 18.8%) and (2.8%, 10%) in terms of labelling and grasping success rate, respectively. Supplementary material is available at https://sites.google.com/view/synthetic-dataset-generation.Comment: Accepted for 2024 10th International Conference on Mechatronics and Robotics Engineering (ICMRE
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