Intelligent robotic systems are becoming essential for inspections and measurements in harsh environments. This article presents the design of an omnidirectional robotic platform for tunnel inspection with spatial limitations. This robot was born from the need to automate the surveillance process of the Super Proton Synchrotron (SPS) accelerator of the European Organization for Nuclear Research (CERN), where there is remaining radiation. The accelerator is located within a tunnel that is divided by small doors of 400 × 200 mm dimensions, through which the robot has to cross. The designed robot brings a robotic arm, and the needed devices to carry out the inspection. Thanks to this design, the robot application may vary by replacing certain devices and tools. In addition, this paper presents the kinematic and dynamic control models for the robotic platform.

This paper presents a fully original algorithm of graph SLAM developed for multiple environments—in particular, for tunnel applications where the paucity of features and the difficult distinction between different positions in the environment is a problem to be solved. This algorithm is modular, generic, and expandable to all types of sensors based on point clouds generation. The algorithm may be used for environmental reconstruction to generate precise models of the surroundings. The structure of the algorithm includes three main modules. One module estimates the initial position of the sensor or the robot, while another improves the previous estimation using point clouds. The last module generates an over-constraint graph that includes the point clouds, the sensor or the robot trajectory, as well as the relation between positions in the trajectory and the loop closures.

Climbing robots play an essential role in performing inspection work in civil infrastructures. These tasks require autonomous robots with competitive costs and the ability to adapt to different types of environments. This article presents ROMERIN, a new concept of a modular legged climbing robot where each leg is an autonomous robotic module in terms of processing capacity, control, and energy. The legs are equipped with suction cups that allow the robot to adhere to different types of surfaces. The proposed design allows the creation of climbing robots with a different number of legs to perform specific inspection tasks. Although each of the legs acts as an independent robot, they have the ability to share information and energy. The proposed control concept enables the development of climbing robots with the ability to adapt to different types of inspection tasks and with resilience characteristics. This article includes a description of the mechatronic design, the kinematics of the seven degree-of-freedom robotic legs, including the adhesion system, and the architecture of the control and simulation system. Finally, we present experimental results to test the modularity concept, mechanical design, and electronics using a four-legged robot configuration. We analyze the performance of the gripping system in different situations on four different surfaces and the behavior of the control architecture for two different robot body trajectories.

Robotic control is a fundamental part of autonomous robots. Modular legged and climbing robots are complex machines made up of a variety of subsystems, ranging from a single robot with simple legs to a complex system composed of multiple legs (or modules) with computing power and sensitivity. Their complexity, which is increased by the fact of needing elements for climbing, makes a correct structure crucial to achieve a complete, robust, and versatile system during its operation. Control architectures for legged robots are distinguished from other software architectures because of the special needs of these systems. In this paper, we present an original classification of modular legged and climbing robots, a comprehensive review of the most important control architectures in robotics, focusing on the control of modular legged and climbing robots, and a comparison of their features. The control architecture comparison aims to provide the analytical tools necessary to make informed decisions tailored to the specific needs of your robotic applications. This article includes a review and classification of modular legged and climbing robots, breaking down each category separately.

MoCLORA (Modular Climbing-and-Legged Robotic Organism Architecture) is a software framework for climbing bio-inspired robotic organisms composed of modular robots (legs). It is presented as a modular low-level architecture that coordinates the modules of an organism with any morphology, at the same time allowing exchanges between the physical robot and its digital twin. It includes the basic layers to control and coordinate all the elements, while allowing adding new higher-level components to improve the organism’s behavior. It is focused on the control of both the body and the legs of the organism, allowing for position and velocity control of the whole robot. Similarly to insects, which are able to adapt to new situations after the variation on the capacity of any of their legs, MoCLORA allows the control of organisms composed of a variable number of modules, arranged in different ways, giving the overall system the versatility to tackle a wide range of tasks in very diverse environments. The article also presents ROMERIN, a modular climbing and legged robotic organism, and its digital twin, which allows the creation of different module arrangements for testing. MoCLORA has been tested and validated with both the physical robot and its digital twin.

In this paper, we present a fully original control architecture for legged-and-climber robots that is level-based, hierarchical, and centralized. The architecture gives the robots the ability to perform self-reconfiguration after unforeseen leg failures, because it can control this kind of robot with different numbers of legs. The results show the capability of performing movements in any direction and inclination planes. The components and functionalities of the developed control architecture for these robots are described, and, the architecture’s performance is tested on the ROMHEX robot.