_... '.' . . : : : " . .W e present an algorithm for planning safe navigation strategies for biped robots moving in obstaclecluttered environments. R o m a discrete set of plausible statieally-stable, single-step motions, a forward dynamic programming approach is used to compute a sequence of feasible footstep locations. In contrast to existing navigation strategies for mobile robots, our method is a global method that takes into account the unique ability of legged robots such as bipedal humanoids to tmverse obstacles by stepping over them. Heuristics designed to minimize the number and complexity of the step motions are used to encode cost functions used for searchang a footstep transition graph. We show prelimina y results of an experimental implementation of the algorithm using a model of the H6 humanoid navigating on an ofice poor littered with obstacles.
We present an approach to path planning for humanoid robots that computes dynamically-stable, collision-free trajectories from full-body posture goals. Given a geometric model of the environment and a statically-stable desired posture, we search the configuration space of the robot for a collision-free path that simultaneously satisfies dynamic balance constraints. We adapt existing randomized path planning techniques by imposing balance constraints on incremental search motions in order to maintain the overall dynamic stability of the final path. A dynamics filtering function that constrains the ZMP (zero moment point) trajectory is used as a post-processing step to transform statically-stable, collision-free paths into dynamically-stable, collision-free trajectories for the entire body. Although we have focused our experiments on biped robots with a humanoid shape, the method generally applies to any robot subject to balance constraints (legged or not). The algorithm is presented along with computed examples using the humanoid robot "H6".
Based on a pharmacokinetic model proposed by Jusko, which assumes that the cell killing action of cell cycle phase-non-specific agents occurs as a bimolecular reaction depending on drug concentration and cell density, we derived a cell kill kinetic equation for these drugs, including the decomposition constant in culture medium. This equation revealed that the cell killing activity of these drugs depends on the value of concentration x exposure time or the area under the drug concentration--time curve (AUC). It was also clarified that the curves for concentration--exposure time necessary for 90% cell kill on a log scale simulated on the basis of the equation differ according as whether drugs are stable or unstable in the culture medium, being expected to be linear with a slope of -1 in the former case, and to take the form of an asymptotic curve in the latter. For three cell cycle phase-non-specific agents, mitomycin C (MMC), 1-(4-amino-2-methylpyrimidine-5-yl)-methyl-3-(2-chloroethyl)3-nitrosoure a hydro-chloride (ACNU), and nitrogen mustard (HN2), we assessed the concentrations necessary for 90% cell kill (IC90) with various exposure times and the degradation rate constants under the culture conditions used. MMC was quite stable during the incubation, while ACNU and HN2 were unstable. When IC90's and exposure times were plotted on the above-mentioned graph, a linear relationship with a slope of -1 was seen for MMC, while for ACNU and HN2 the anticipated asymptotic curves resulted. We also ascertained that the decomposition constants for ACNU and HN2 expected on the basis of these curves showed a good agreement with the corresponding experimentally observed values. These results indicate that the cell killing action of cell cycle phase-non-specific drugs can be well described by a pharmacodynamic model and equation employing their decomposition constants and are dependent on the concentration-time product.
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