Abstract-We present a novel algorithm for path planning that avoids occlusions of a visual target for an "eye-in-hand" sensor on an articulated robot arm. We compute paths using a probabilistic roadmap to avoid collisions between the robot and obstacles, while penalizing trajectories that do not maintain line-of-sight. The system determines the space from which line-of-sight is unimpeded to the target (the visible region) using the method described in [11]. We assign penalties to trajectories within the roadmap proportional to the distance the camera travels while outside the visible region. Using Dijkstra's algorithm, we compute paths of minimal occlusion (maximal visibility) through the roadmap. In our experiments, we compare a shortest-distance path to the minimal-occlusion path and discuss the impact of the improved visibility.
Abstract-This paper describes the development of DeepGreen, an intelligent robotic system that is currently in development to play competitive pool against a proficient human opponent. The design philosophy and the main system components are presented, and the progress to date is summarized. We also address a common misconception about the game of pool, i.e. that it is purely a game of physical skill, requiring little or no intelligence or strategy. We explain some of the difficulties in developing a vision-based system with a high degree of positional accuracy. We further demonstrate that even if perfect accuracy were possible, it is still beneficial and necessary to play strategically.
A 3D numerical block of a rock composed of spherical particles embedded into a matrix is simulated by a computer program which allows also to deform the block with novolume change in a coaxial strain regime for different values of the strain ellipsoid: plane strain, constriction and flattening. The influence of several parameters such as size of particles, minimum distance allowed between two particles, particle/matrix viscosity ratio , particle distribution (anticlustering, graded bedding, clustering) are discussed in order to use the centroid method (Fry's method) for strain measurement . Inside the deformed block, calculated and automatically drawn sections are cut parallel to the three principal strain planes (XY , YZ, XZ). Using the centroid method, the finite strain is calculated by combining the principal strain planes, and compared to the true strain ellipsoid fixed by the initial conditions of simulation. Graphic images are also plotted from the numerical sections . They are investigated by image analysis, centroid are extracted and strain ellipses and ellipsoid calculated . The good correlation between the real strain ellipsoid, the numerical strain ellipsoid and the calculated strain ellipsoid is assessed. Lastly, the centroid method is applied to naturally deformed samples in which data acquisition of centroid is made by image analysis.
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