Climbing robots are characterized by a secure surface coupling that is designed to prevent falling. The robot coupling ability is assured by an adhesion method leading to nonlinear dynamic models with time-varying parameters that affect the robot’s mobility. Additionally, the wheel friction and the force of gravity force are also relevant issues that can compromise the climbing ability if they are not well modeled. This work presents a model-based torque controller for velocity tracking in a four-wheeled climbing robot specially designed to inspect storage tanks. The model-based controller (MPC) compensates for the effects of nonlinearities due to the forces of gravity, friction, and adhesion through the dynamic and kinematic modeling of the climbing robot. Dynamic modeling is based on the Lagrange-Euler approach, which allows a better understanding of how forces and torques affect the robot’s movement. Besides, an analysis of the interaction force between the robot and the contact surface is proposed, since this force affects the motion of the climbing robot according to spatial orientation. Finally, simulations are carried out to examine the robot’s dynamics during the climbing movement, and the MPC is validated through the redrobot simulator V-REP and practical experiments. The presented results highlight the compensation of the nonlinear effects due to the robot’s climbing motion by the proposed MPC controller.

This work presents the use of multiple mobile robots to perform a common transportation task. The main objective is to perform a navigation with a shared cargo, which allows the transport of objects with high payload or high sizes. Two robots are virtually linked through two Fuzzy controllers, one to control distance and another for orientation. A depth camera on the trailer's robot is used to measure the distance and orientation of the leader robot. The proposed approach is experimentally validated with two standard Pioneer mobile robots that collaboratively carry a large box.

This paper presents a novel approach to inspection planning in spherical storage tanks by an autonomous climbing robot. The objective is the automatic extraction of some environment characteristics, by robot, to predict the tank dimensions and robot localization. Three distinct perception sources (long range laser rangefinder, light detection and ranging, and depth camera) are used to predict a 3D occupancy grid wrapping calculated tank. From this grid, a path for tank inspection is computed that ensuring a complete icon at the entire tank surface. This scanning must consider kinematic constraints of magnetic wheels and NDT standard. The approach is evaluated in four LPG's spherical tanks virtually designed with same characteristics that real tank projects.