By Robert Balthazaar
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Additional resources for Active Dreaming: The Key to Power
To determine the domain of attraction, we determined all the orientations of the robot for which our empirical computation of the time derivative of the Lyapunov function was positive. We then start at the level surface V = c for c very large and slowly decrease c until arriving at a level surface where V˙ < 0 for every point in its interior except at the goal. The volume defined by the interior of the level surface defines the domain of attraction for this 3 degrees of freedom system. Figure 5(a) shows this level surface and nearby points where V˙ > 0.
Distinctive Image Features from Scale-Invariant Keypoints. Int. J. Comput. : An Invitation to 3-D Vision: From Images to Geometric Models. Interdisciplinary Applied Mathematics. : EGT for Multiple View Geometry and Visual Servoing: Robotics Vision with Pinhole and Panoramic Cameras. IEEE Robot. Autom. Mag. : Image-based Visual Servoing with Central Catadioptric Camera. Int. J. Robot. Res. : Planar Catadioptric Stereo: Single and Multi-View Geometry for Calibration and Localization. In: Proc. IEEE Int.
Using the modified notation, the signal at any translated position is related to the signal at the goal I(w, x(t)) = I(w − x(t), 0) = I0 (w − x(t)). 3) = K(w)I0 (w − x(t))dw, I and the kernel-projected value at the goal is ξ 0 = ξ at x0 . The dimension n refers to the number of kernels being used such that the kernels represent a function K : R2 → Rn . 3) can be written as ξ= I K(w ¯ + x(t))I0 (w)d ¯ w. 4) show that the the kernel-projected value is the same for the fixed kernel with an image taken after the camera has been moved and a kernel shifted in the opposite direction with the goal image.
Active Dreaming: The Key to Power by Robert Balthazaar