28 research outputs found

    Online Tool Selection with Learned Grasp Prediction Models

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    Deep learning-based grasp prediction models have become an industry standard for robotic bin-picking systems. To maximize pick success, production environments are often equipped with several end-effector tools that can be swapped on-the-fly, based on the target object. Tool-change, however, takes time. Choosing the order of grasps to perform, and corresponding tool-change actions, can improve system throughput; this is the topic of our work. The main challenge in planning tool change is uncertainty - we typically cannot see objects in the bin that are currently occluded. Inspired by queuing and admission control problems, we model the problem as a Markov Decision Process (MDP), where the goal is to maximize expected throughput, and we pursue an approximate solution based on model predictive control, where at each time step we plan based only on the currently visible objects. Special to our method is the idea of void zones, which are geometrical boundaries in which an unknown object will be present, and therefore cannot be accounted for during planning. Our planning problem can be solved using integer linear programming (ILP). However, we find that an approximate solution based on sparse tree search yields near optimal performance at a fraction of the time. Another question that we explore is how to measure the performance of tool-change planning: we find that throughput alone can fail to capture delicate and smooth behavior, and propose a principled alternative. Finally, we demonstrate our algorithms on both synthetic and real world bin picking tasks.Comment: 14 pages (including the cover page), 5 Figures, Technical Report, OSARO In

    A Modified Electrochemical Model to Account for Mechanical Effects Due to Lithium Intercalation and External Pressure

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    For a battery cell, both the porosity of the electrodes/separator and the transport distance of charged species can evolve due to mechanical deformation arising from either lithium intercalation-induced swelling and contraction of the active particles or externally applied mechanical loading. To describe accurately the coupling between mechanical deformation and the cell\u27s electrochemical response, we extend Newman\u27s DualFoil model to allow variable, non-uniform porosities in both electrodes and the separator, which are dynamically updated based on the electrochemical and mechanical states of the battery cell. In addition, the finite deformation theory from continuum mechanics is used to modify the electrochemical transport equations to account for the change of the charged species transport distance. The proposed coupled electrochemomechanical model is tested with a parameterized commercial cell. Our simulation results confirm that mass conservation is satisfied with the new formulation. We further show that mechanical effects have a significant impact on the cell\u27s electrochemical response at high charge/discharge rates

    Aethionema arabicum dimorphic seed trait resetting during transition to seedlings

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    The transition from germinating seeds to emerging seedlings is one of the most vulnerable plant life cycle stages. Heteromorphic diaspores (seed and fruit dispersal units) are an adaptive bet-hedging strategy to cope with spatiotemporally variable environments. While the roles and mechanisms of seedling traits have been studied in monomorphic species, which produce one type of diaspore, very little is known about seedlings in heteromorphic species. Using the dimorphic diaspore model Aethionema arabicum (Brassicaceae), we identified contrasting mechanisms in the germination responses to different temperatures of the mucilaginous seeds (M+ seed morphs), the dispersed indehiscent fruits (IND fruit morphs), and the bare non-mucilaginous M− seeds obtained from IND fruits by pericarp (fruit coat) removal. What follows the completion of germination is the pre-emergence seedling growth phase, which we investigated by comparative growth assays of early seedlings derived from the M+ seeds, bare M− seeds, and IND fruits. The dimorphic seedlings derived from M+ and M− seeds did not differ in their responses to ambient temperature and water potential. The phenotype of seedlings derived from IND fruits differed in that they had bent hypocotyls and their shoot and root growth was slower, but the biomechanical hypocotyl properties of 15-day-old seedlings did not differ between seedlings derived from germinated M+ seeds, M− seeds, or IND fruits. Comparison of the transcriptomes of the natural dimorphic diaspores, M+ seeds and IND fruits, identified 2,682 differentially expressed genes (DEGs) during late germination. During the subsequent 3 days of seedling pre-emergence growth, the number of DEGs was reduced 10-fold to 277 root DEGs and 16-fold to 164 shoot DEGs. Among the DEGs in early seedlings were hormonal regulators, in particular for auxin, ethylene, and gibberellins. Furthermore, DEGs were identified for water and ion transporters, nitrate transporter and assimilation enzymes, and cell wall remodeling protein genes encoding enzymes targeting xyloglucan and pectin. We conclude that the transcriptomes of seedlings derived from the dimorphic diaspores, M+ seeds and IND fruits, undergo transcriptional resetting during the post-germination pre-emergence growth transition phase from germinated diaspores to growing seedlings

    Neuronal Control of Metabolism through Nutrient-Dependent Modulation of Tracheal Branching

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    SummaryDuring adaptive angiogenesis, a key process in the etiology and treatment of cancer and obesity, the vasculature changes to meet the metabolic needs of its target tissues. Although the cues governing vascular remodeling are not fully understood, target-derived signals are generally believed to underlie this process. Here, we identify an alternative mechanism by characterizing the previously unrecognized nutrient-dependent plasticity of the Drosophila tracheal system: a network of oxygen-delivering tubules developmentally akin to mammalian blood vessels. We find that this plasticity, particularly prominent in the intestine, drives—rather than responds to—metabolic change. Mechanistically, it is regulated by distinct populations of nutrient- and oxygen-responsive neurons that, through delivery of both local and systemic insulin- and VIP-like neuropeptides, sculpt the growth of specific tracheal subsets. Thus, we describe a novel mechanism by which nutritional cues modulate neuronal activity to give rise to organ-specific, long-lasting changes in vascular architecture
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