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subproblems: (1) planning a path to avoid collision with static obstacles and (2) planning the velocity along the path to avoid collision with moving obsta cles. We call thefirst subproblem the path planning ...
Contributions The contributions of this paper are towards improving the computational efficiency of path - planning algorithms for mobile vehicle applications with time-varying changes in the vehicle’s environment ...
is inversely proportional to the gene’s speed. This means that the fastest genes are only active towards the end of the differentiation trajectory . The resulting differentiation trajectory has high velocity ...
) = (0, 0). Under control conditions wildtype neutrophils migrate efficiently along the CXCL1 (KC) gradient towards the positive y-axis (Fig 1A). This is indicated by the black line which depicts the mean ...
(e.g. planning noise) also affects saccades. Noise entering upstream from the motor system would cause variability of saccade trajectories ; even in the absence of motor-noise (i.e. noise entering ...
uses a wavelet-based decomposition for easing the computational load of a multiresolution path planner. Trajectory planning methods, on the other hand, search for routes that respect the movement ...
amplitude towards the tip. For both waves we chose the same wavelength . We kept the frequency of the tip-to-base wave fixed and varied the frequency or velocity of the base-to-tip wave. Fig. 4 plots ...
they can be manipulated to optimize passage efficiency . The most widely used stimulus in fish orientation IBMs, regardless of whether the model considers upstream or downstream fish migration, is velocity ...
) variables, while the latter determines the smoothness of random fluctuations (i.e. the correlations between position, velocity and subsequent temporal derivatives). The point of this decomposition ...
optimization problems that are amenable to computationally efficient supervised learning techniques. We present FIGR (Fast Inference of Gene Regulation), a novel classification-based inference approach ...
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