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The task of navigation in an unknown environment is an important feature for any autonomous robot. From a predetermined path, the robot must be able to accomplish its trajectory using data processed by itself. Many techniques have been studying in order to provide a robot this capability for instance navigation using landmarks, navigation based in maps of the environment and others. Here, the technique of Visual Path Tracking has been selected and deployed to control the robot trajectory. It consists of tracking a desired object in a sequence of frames to support the robot accomplish its trajectory.
The ROS Master registers the services and then the camera node request images from camera in a predetermined frequency. These images are processed in order to detect target objects and the results are inputted into the object and robot localization node and it estimates the robot and object pose. The robot’s and object’s pose are matrices that contain the pose of both elements and these matrices are inputted into the path tracking controller node, that calculates the distance to be traveled from the current robot pose to the object detected and it outputs a velocity message that is sent to the Command Velocity Node (CMD), which controls the robots motors directly.
While the process of navigation is going on, the object pose is available to be stored into the database. The robot global pose is used to compose the history of measurement and it is available in the moment that a defect is detected. Likewise, when the camera node is carried out, the same sequence of images captured by the camera is processed by CDA and CMA in order to detect cracks in objects surface and also to measure them. When cracks are detected, the node then outputs them as a matrix that contains its respective dimension [width, length] and also the crack center coordinate in X-axis and Y -axis respectively.
Finally, the database node has been deployed in order to store all data acquired in the field. In the moment that a crack is detected and measured, the database node receives a message, which allows a user to see data such as the object identification, object position, crack identification and crack measurement in order to create the measurement history.
The autonomous robot system proposed produces a very large amount of run-time data (acquired from sensors or generated by actuators) that need to be processed so it can serve as the basis for decision-making or parameter estimation. Since the data may be useful later (for instance to analyze faults or evaluate the robots performance), it needs to be stored and accessible through efficient and flexible querying mechanisms.
A Client/Server architecture is then used (a user-interface front-end and a database server back-end). This architecture ensures data security and allows parallel access for several users. It also offers a way to make data available both within a local area network (intranet) and in the internet to support users.
The architecture is based on a SQL server, which holds the database tables. The advantage of a SQL compatible database server lies in its performance scalability. It also has interfaces to different programming languages and it allows very complex programming with comprehensive possibilities.
The database consists of four tables. The Robot Global Pose table holds the pose of the robot. The Object Pose table stores the pose of objects that contain cracks and an identifier of object .The Crack table holds the crack detected the position of its center relative to the object and an identifier of the crack. Finally, the Crack History table holds the crack measurement as well as an image in Portable Network Graphics (PNG) format for further verification. The history is associated with date, time of measurement etc
The use of autonomous robot system for monitoring the structural health of buildings is fast, reliable and accurate than traditional methods to inspect civil infrastructure. Therefore, the application of autonomous system to monitor automatically the structural health monitoring from the moment that the measurement is going on in the field until the management of structures maintenance, has many technical and financial advantage.
For civil structures, visual inspection by a human could be replaced by more precise and fast methods based on processing data provided by cameras, lasers, sonars, and other sensors and can be used in various applications such as to map abandoned mines, a robot for inspection of pipes ,and system for bridge inspections using vision, laser and ultrasound sensors.
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