The use of reticular structures, which are composed of a number of beams or bars closely intertwined, is widespread nowadays in the construction of all types of fastening and support components for different infrastructures. They are especially indicated in metal bridges but also in roofs of hangars and spacious industrial buildings. They are generally formed by a set of highly interlinked and interconnected bars, joined together by nodes (either rigid or articulated), forming a three-dimensional structural mesh. The execution of both inspection and maintenance tasks on this type of reticular structures is especially challenging owing to (a) the access problems because of the high interconnection of the bars through the nodes and (b) the complexity of going through paths that permit moving from one starting point to a target point while traversing these structural nodes.

Aerial vehicles have been considered along the past few years as a possible solution to automate these inspection and maintenance tasks on reticular three-dimensional structures. However, the high complexity of such structures (often including narrow gaps between nodes and bars and with a strongly heterogeneous distribution) limits the use of this type of aerial vehicles, since they could not enter the different internal locations of the structure that are not easily accessible. Another of the limitations of this type of vehicles is their limited manipulation capacity while they are in the air.

The present research project focuses on this field. The project will explore the possibility of using robotic units that can move along these reticular structures in such a way that they can navigate through them with 6 degrees of freedom and traverse the reticular nodes present in them, regardless of their arrangement, layout and 3D configuration of the mesh. To address these inspection and / or maintenance tasks, this research project proposes the analysis, design and implementation of hybrid robots. They will consist of simple modules with few degrees of freedom, either with serial or parallel structure, designed in such a way that, when combined into hybrid robots, they can effectively navigate through these reticular structures despite all the challenging issues they present. In addition to analyzing these robots in depth, both from the kinematic and dynamic point of view, we propose to analyze and demonstrate their ability to navigate through such reticular workspaces, negotiating any possible arrangement of reticular nodes present in such structures.

Finally, it is essential to have a sufficiently precise model of the reticular structure in which these modular robots have to operate and to estimate efficiently their position and orientation in this environment. Considering the experience of the members of the research team in previous projects, the present project also proposes performing the reconstruction of these environments (three-dimensional grid structures), based on the fusion of the information provided by both range and visual sensors in a 360o field of perception around the robot. To achieve this objective, deep learning techniques will be used to efficiently process the high amount of data provided by the sensors.


Project PID2020-116418RB-I00 funded by MCIN/AEI/10.13039/501100011033.