Abstract
This work presents a solution to localize Unmanned Autonomous Vehicles with respect to pipes and other cylindrical elements found in inspection and maintenance tasks both in industrial and civilian infrastructures. The proposed system exploits the different features of vision and laser based sensors, combining them to obtain accurate positioning of the robot with respect to the cylindrical structures. A probabilistic (RANSAC-based) procedure is used to segment possible cylinders found in the laser scans, and this is used as a seed to accurately determine the robot position through a computer vision system. The priors obtained from the laser scan registration help to solve the problem of determining the apparent contour of the cylinders. In turn this apparent contour is used in a degenerate quadratic conic estimation, enabling to visually estimate the pose of the cylinder.
Highlights
For a long time robots and automata can be found in industrial and civilian operations as part of complex systems presenting some degree of automation
An example of such elements would be pipes and canalizations, especially in heavy industries, where kilometers of pipes have to be periodically inspected. These pipes and tubes are common structures in industry and in urban environments, and can be frequently found in hard to reach areas. This poses a problem for the mentioned monitoring and maintenance operations, as those operations are commonly performed by human personnel or ground-based unmanned vehicles (UGVs) with great efficiency, become expensive and exceptionally risky in inaccessible areas
Assuming that there is a cylindrical pipe, which can be described as a SHCC, C, and a coordinate frame centered in the sensor L, with δL T denoting the homogenous transformation from a world origin õ to this LiDAR frame, the Random Sample Consensus (RANSAC) process tries to fit a SHCC
Summary
For a long time robots and automata can be found in industrial and civilian operations as part of complex systems presenting some degree of automation. These pipes and tubes are common structures in industry and in urban environments, and can be frequently found in hard to reach areas This poses a problem for the mentioned monitoring and maintenance operations, as those operations are commonly performed by human personnel or ground-based unmanned vehicles (UGVs) with great efficiency, become expensive and exceptionally risky in inaccessible areas. In such scenarios, operations with humans in high and/or hard to reach areas generally imply shutting off ordinary operation, building temporary scaffolds, and following complex safety protocols and procedures to minimize risks. The experimental results obtained to evaluate the different methods are detailed in Section 6, after a brief description of the different experimental setups used
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