Andrew Dornbush

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Efficient footstep planning for humanoid navigation through cluttered environments is still a challenging problem. Many obstacles create local minima in the search space, forcing heuristic planners such as A* to expand large areas. The goal of this work is to efficiently compute long, feasible footstep paths. For navigation, finding the optimal path(More)
Path planning in dynamic environments with moving obstacles is computationally complex since it requires modeling time as an additional dimension. While in other domains there are state dominance relationships that can significantly reduce the complexity of the search, in dynamic environments such relationships do not exist. This paper presents a novel(More)
Three tetracycline analogues, tetracycline (TC), chlortetracycline (CTC) and oxytetracycline (OTC) have been used extensively in man and are well established as effective antimicrobial agents. Recently a fourth analogue, demethylchlortetracycline (DMCT) was described (1) and is being introduced for clinical use.' The structural formulas of these four(More)
LL-BM123beta, gamma1 and gamma2 are three new antibiotics produced by fermentation of an unidentified species of Nocardia. These strongly basic, water soluble compounds were isolated from the culture filtrate by CM-Sephadex ion-exchange and carbon chromatography. All three antibiotics are active against both gram-positive and gram-negative bacteria. A(More)
Robots operating in real world environments need to find motion plans quickly. Robot motion should also be efficient and, when operating among people, predictable. Minimizing a cost function, e.g. path length, can produce short, reasonable paths. Anytime planners are ideal for this since they find an initial solution quickly and then improve solution(More)