Real-time outline mapping for mobile blind robots

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Liu, Juan J.
Zhang, Ying
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Real-time outline mapping for mobile blind robots

Mapping is important for mobile robots in unknown environments. However, existing work largely relies on long-range sensors such as expensive laser range finders and cameras. Little has been done for robots with only short-range sensors such as bumpers or wall sensors. In this paper, we fill in the gap and propose a method for real-time indoor mapping for blind robots, i.e. robots that have only short-range sensors. Several key problems for mapping are addressed in this paper: (1) generating map from a single robot's odometry and short-range sensor data, (2) combining and collating maps from multiple robots to generate a coherent bigger map, and (3) detecting loops in the map and performing loop closure. The method has been implemented on iRobot Create and tested in hallways of office buildings. Experimental results have shown that the system is robust to noisy odometry and obstacles along the walls.

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