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.
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