3 research outputs found

    Online Exploration of an Unknown Region of Interest with a Team of Aerial Robots

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    In this paper, we study the problem of exploring an unknown Region Of Interest (ROI) with a team of aerial robots. The size and shape of the ROI are unknown to the robots. The objective is to find a tour for each robot such that each point in the ROI must be visible from the field-of-view of some robot along its tour. In conventional exploration using ground robots, the ROI boundary is typically also as an obstacle and robots are naturally constrained to the interior of this ROI. Instead, we study the case where aerial robots are not restricted to flying inside the ROI (and can fly over the boundary of the ROI). We propose a recursive depth-first search-based algorithm that yields a constant competitive ratio for the exploration problem. Our analysis also extends to the case where the ROI is translating, \eg, in the case of marine plumes. In the simpler version of the problem where the ROI is modeled as a 2D grid, the competitive ratio is 2(Sr+Sp)(R+⌊log⁑RβŒ‹)(Srβˆ’Sp)(1+⌊log⁑RβŒ‹)\frac{2(S_r+S_p)(R+\lfloor\log{R}\rfloor)}{(S_r-S_p)(1+\lfloor\log{R}\rfloor)} where RR is the number of robots, and SrS_r and SpS_p are the robot speed and the ROI speed, respectively. We also consider a more realistic scenario where the ROI shape is not restricted to grid cells but an arbitrary shape. We show our algorithm has 2(Sr+Sp)(18R+⌊log⁑RβŒ‹)(Srβˆ’Sp)(1+⌊log⁑RβŒ‹)\frac{2(S_r+S_p)(18R+\lfloor\log{R}\rfloor)}{(S_r-S_p)(1+\lfloor\log{R}\rfloor)} competitive ratio under some conditions. We empirically verify our algorithm using simulations as well as a proof-of-concept experiment mapping a 2D ROI using an aerial robot with a downwards-facing camera.Comment: 13 pages, 11 figures, Submitted to the International Journal of Robotics Researc

    Exploring Grid Polygons Online

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    We investigate the exploration problem of a short-sighted mobile robot moving in an unknown cellular room. To explore a cell, the robot must enter it. Once inside, the robot knows which of the 4 adjacent cells exist and which are boundary edges. The robot starts from a specified cell adjacent to the room's outer wall; it visits each cell, and returns to the start. Our interest is in a short exploration tour; that is, in keeping the number of multiple cell visits small. For abitrary environments containing no obstacles we provide a strategy producing tours of length S <= C + 1/2 E - 3, and for environments containing obstacles we provide a strategy, that is bound by S <= C + 1/2 E + 3H + WCW - 2, where C denotes the number of cells-the area-, E denotes the number of boundary edges-the perimeter-, and H is the number of obstacles, and WCW is a measure for the sinuosity of the given environment.Comment: 49 pages, 45 figure

    Exploring an Unknown Cellular Environment

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    We investigate the exploration problem of a short-sighted mobile robot moving about in an unknown cellular room. In order to explore a cell, the robot must enter it. Once inside, the robot knows which of the 4 adjacent cells exist and which are boundary edges. The robot starts from a specified cell adjacent to the room&apos;s outer wall; it visits each cell, and returns to the start. Our interest is in a short exploration tour, that is, in keeping the number of multiple cell visits small. For abitrary environments containing obstacles we provide a strategy producing tours of length S # C+ 1 2 E+H- 3, where C denotes the number of cells---the area---, E denotes the number of boundary edges---the perimeter---, and H is the number of obstacles
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