28 research outputs found

    Motion Planning via Manifold Samples

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    We present a general and modular algorithmic framework for path planning of robots. Our framework combines geometric methods for exact and complete analysis of low-dimensional configuration spaces, together with practical, considerably simpler sampling-based approaches that are appropriate for higher dimensions. In order to facilitate the transfer of advanced geometric algorithms into practical use, we suggest taking samples that are entire low-dimensional manifolds of the configuration space that capture the connectivity of the configuration space much better than isolated point samples. Geometric algorithms for analysis of low-dimensional manifolds then provide powerful primitive operations. The modular design of the framework enables independent optimization of each modular component. Indeed, we have developed, implemented and optimized a primitive operation for complete and exact combinatorial analysis of a certain set of manifolds, using arrangements of curves of rational functions and concepts of generic programming. This in turn enabled us to implement our framework for the concrete case of a polygonal robot translating and rotating amidst polygonal obstacles. We demonstrate that the integration of several carefully engineered components leads to significant speedup over the popular PRM sampling-based algorithm, which represents the more simplistic approach that is prevalent in practice. We foresee possible extensions of our framework to solving high-dimensional problems beyond motion planning.Comment: 18 page

    Anti-inflammatory effects of a novel, potent inhibitor of poly (ADP-ribose) polymerase

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    OBJECTIVE AND DESIGN: Oxygen- and nitrogen-derived free radicals and oxidants play an important role in the pathogenesis of various forms of inflammation. Recent work emphasizes the importance of oxidant-induced DNA strand breakage and activation of the nuclear enzyme poly(ADP-ribose) polymerase (PARP) in the pathogenesis of various inflammatory diseases. We have recently demonstrated the efficacy of PJ34, a novel, potent phenanthridinone derivative PARP inhibitor, in rodent models of diabetic vascular dysfunction and stroke. Here we tested the efficacy of PARP inhibition in various models of local inflammation in rodents. MATERIALS AND METHODS: PJ34 (at doses of 0.03-30 mg/kg) was tested in rats and mice subjected to standard models of inflammation, with relevant parameters of inflammation measured using standard methods. RESULTS: PJ34 treatment (s.c, i.p. and i.v.) dose-dependently suppressed neutrophil infiltration and nitric oxide (but not KC and IL-1beta) production in peritonitis. In a model of systemic endotoxemia, PJ34 pretreatment significantly reduced plasma levels of TNF-alpha, IL-1beta and nitrite/nitrate (breakdown products of nitric oxide) production. PJ34 treatment (oral gavage) induced a significant suppression of the inflammatory response in dextran sulfate colitis, multiple low dose streptozotocin diabetes and cyclophosphamide-accelerated autoimmune diabetes in the non-obese diabetic mice, and reduced the degree of mononuclear cell infiltration into the iris in an endotoxin-induced uveitis model. Delaying the start of PJ34 administration in the colitis model conferred significant protective effects, while in the arthritis model the post-treatment paradigm lacked protective effects. CONCLUSIONS: PJ34 provides significant, dose-dependent, anti-inflammatory effects in a variety of local inflammation models. Some of its actions are maintained in the post-treatment regimen and/or after discontinuation of treatment. We conclude that PARP inhibition offers a powerful means for reducing the severity of various forms of local inflammatory responses
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