69 research outputs found
TransPose: 6D Object Pose Estimation with Geometry-Aware Transformer
Estimating the 6D object pose is an essential task in many applications. Due
to the lack of depth information, existing RGB-based methods are sensitive to
occlusion and illumination changes. How to extract and utilize the geometry
features in depth information is crucial to achieve accurate predictions. To
this end, we propose TransPose, a novel 6D pose framework that exploits
Transformer Encoder with geometry-aware module to develop better learning of
point cloud feature representations. Specifically, we first uniformly sample
point cloud and extract local geometry features with the designed local feature
extractor base on graph convolution network. To improve robustness to
occlusion, we adopt Transformer to perform the exchange of global information,
making each local feature contains global information. Finally, we introduce
geometry-aware module in Transformer Encoder, which to form an effective
constrain for point cloud feature learning and makes the global information
exchange more tightly coupled with point cloud tasks. Extensive experiments
indicate the effectiveness of TransPose, our pose estimation pipeline achieves
competitive results on three benchmark datasets.Comment: 10 pages, 5 figures, IEEE Journa
Unbiased Directed Object Attention Graph for Object Navigation
Object navigation tasks require agents to locate specific objects in unknown
environments based on visual information. Previously, graph convolutions were
used to implicitly explore the relationships between objects. However, due to
differences in visibility among objects, it is easy to generate biases in
object attention. Thus, in this paper, we propose a directed object attention
(DOA) graph to guide the agent in explicitly learning the attention
relationships between objects, thereby reducing the object attention bias. In
particular, we use the DOA graph to perform unbiased adaptive object attention
(UAOA) on the object features and unbiased adaptive image attention (UAIA) on
the raw images, respectively. To distinguish features in different branches, a
concise adaptive branch energy distribution (ABED) method is proposed. We
assess our methods on the AI2-Thor dataset. Compared with the state-of-the-art
(SOTA) method, our method reports 7.4%, 8.1% and 17.6% increase in success rate
(SR), success weighted by path length (SPL) and success weighted by action
efficiency (SAE), respectively.Comment: 13 pages, ready to ACM Mutimedia, under revie
Global perspectives on the energy landscapes of liquids, supercooled liquids, and glassy systems: The potential energy landscape ensemble
In principle, all of the dynamical complexities of many-body systems are
encapsulated in the potential energy landscapes on which the atoms move - an
observation that suggests that the essentials of the dynamics ought to be
determined by the geometry of those landscapes. But what are the principal
geometric features that control the long-time dynamics? We suggest that the key
lies not in the local minima and saddles of the landscape, but in a more global
property of the surface: its accessible pathways. In order to make this notion
more precise we introduce two ideas: (1) a switch to a new ensemble that
removes the concept of potential barriers from the problem, and (2) a way of
finding optimum pathways within this new ensemble. The potential energy
landscape ensemble, which we describe in the current paper, regards the maximum
accessible potential energy, rather than the temperature, as a control
variable. We show here that while this approach is thermodynamically equivalent
to the canonical ensemble, it not only sidesteps the idea of barriers, it
allows us to be quantitative about the connectivity of a landscape. We
illustrate these ideas with calculations on a simple atomic liquid and on the
Kob-Andersen model of a glass-forming liquid, showing, in the process, that the
landscape of the Kob-Anderson model appears to have a connectivity transition
at the landscape energy associated with its mode-coupling transition. We turn
to the problem of finding the most efficient pathways through potential energy
landscapes in our companion paper.Comment: 43 pages, 7 figure
A Systematic Review of Associations between Energy Use, Fuel Poverty, Energy Efficiency Improvements and Health
Energy use in buildings can influence the indoor environment. Studies on green buildings, energy saving measures, energy use, fuel poverty, and ventilation have been reviewed, following the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. The database PubMed was searched for articles published up to 1 October 2020. In total, 68 relevant peer-reviewed epidemiological or exposure studies on radon, biological agents, and chemicals were included. The main aim was to assess current knowledge on how energy saving measures and energy use can influence health. The included studies concluded that buildings classified as green buildings can improve health. More efficient heating and increased thermal insulation can improve health in homes experiencing fuel poverty. However, energy-saving measures in airtight buildings and thermal insulation without installation of mechanical ventilation can impair health. Energy efficiency retrofits can increase indoor radon which can cause lung cancer. Installation of a mechanical ventilation systems can solve many of the negative effects linked to airtight buildings and energy efficiency retrofits. However, higher ventilation flow can increase the indoor exposure to outdoor air pollutants in areas with high levels of outdoor air pollution. Finally, future research needs concerning energy aspects of buildings and health were identified
Energy use and energy saving in buildings and asthma, allergy and sick building syndrome (SBS): a literature review
Energy use in buildings is an important contribution to global CO2 emissions and contributes to global warming. In recent years, there has been concern about creating energy efficiency buildings, green buildings and healthy buildings but this development needs guidance by multidisciplinary scientists and experts. Since energy saving can influence the indoor environment in different ways, epidemiological research is needed in different climate zones to evaluate the health consequences of making the buildings more energy efficient. Epidemiological studies and modelling studies are available on health effects and indoor effects of energy conversation, improved thermal insulation, increased air tightness and creating green buildings. The health-related literature on this issue was reviewed, by searching scientific articles in the medical Database PubMed and in the general database Web of Science as well as Nature database. In this literature review, 53 relevant peer reviewed articles on health effects of energy use and energy saving were found. Most of the studies had investigated residential buildings. One main conclusion from the review is that combined energy efficiency improvements in buildings can be associated with improvement of general health, such as less asthma, allergies, sick building syndrome (SBS) symptoms, respiratory symptoms, and reduced cold-related and heat-related mortality. Moreover, combined energy efficiency improvements can improve indoor air quality, increase productivity and satisfaction and reduce work leave and school absence. Effective heating of buildings can reduce respiratory symptoms and reduce work leave and school absence. However, some potential health problems can occur if increased energy efficiency will reduce ventilation flow. Energy saving by increasing air tightness or reducing ventilation is associated with impaired indoor air quality and negative health effects. In contrast, improved ventilation may reduce SBS, respiratory symptoms and increase indoor air quality. Installation of mechanical ventilation can solve the negative effects of making the building construction in dwellings more air tight. In future research, more studies are needed on health impacts of single energy efficiency improvement methods. Existing studies have mostly used a combination of improvement methods. In addition, modelling software programs should more often be used, since they can take into account effects of different energy efficiency improvement methods on indoor air quality in different types of buildings and in different climates
A Systematic Review of Associations between Energy Use, Fuel Poverty, Energy Efficiency Improvements and Health
Energy use in buildings can influence the indoor environment. Studies on green buildings, energy saving measures, energy use, fuel poverty, and ventilation have been reviewed, following the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. The database PubMed was searched for articles published up to 1 October 2020. In total, 68 relevant peer-reviewed epidemiological or exposure studies on radon, biological agents, and chemicals were included. The main aim was to assess current knowledge on how energy saving measures and energy use can influence health. The included studies concluded that buildings classified as green buildings can improve health. More efficient heating and increased thermal insulation can improve health in homes experiencing fuel poverty. However, energy-saving measures in airtight buildings and thermal insulation without installation of mechanical ventilation can impair health. Energy efficiency retrofits can increase indoor radon which can cause lung cancer. Installation of a mechanical ventilation systems can solve many of the negative effects linked to airtight buildings and energy efficiency retrofits. However, higher ventilation flow can increase the indoor exposure to outdoor air pollutants in areas with high levels of outdoor air pollution. Finally, future research needs concerning energy aspects of buildings and health were identified
Locomotion control of quadruped robots based on workspace trajectory modulations
Designing an effective motion control for legged robots is a challenging task. Inspired by biological concept of central pattern generator, this paper proposes a locomotion control system consisting of a workspace trajectory modulator and a motion engine. The modulator adjusts swinging phase and supporting phase of a leg by adjusting toe positions on a predesigned workspace trajectory, while motion engine generates accurate joint control signals. With body attitude feedback, the modulator adjusts the durations of swinging phase and supporting phase in real time through mutual entrainment. This proposed control system ensures that the robot locomotion is adaptive to various terrains and environments. Extensive experiments using an AIBO robot validate the proposed control scheme and the AIBO adapts its walking patterns according to environmental properties.Published versio
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