Odometry is a computation method that provides a periodic estimation of the relative displacements performed by a mobile robot based on its inverse kinematic matrix, its previous orientation and position, and the estimation of the angular rotational velocity of its driving wheels. Odometry is cumulatively updated from tens to hundreds of times per second, so any inaccuracy in the definition of the inverse kinematic matrix of a robot leads to systematic trajectory errors. This paper proposes a non-parametric calibration of the inverse kinematic (IK) matrix of a three-wheeled omnidirectional mobile robot based on the use of genetic algorithms (GA) to minimize the positioning error registered in a set of calibration trajectories. The application of this non-parametric procedure has provided an average improvement of 82% in the estimation of the final position and orientation of the mobile robot. This is similar to the improvement achieved with analogous parametric methods. The advantage of this non-parametric approach is that it covers a larger search space because it eliminates the need to define feasible physical limits to the search performed to calibrate the inverse kinematic matrix of the mobile robot.

The development of a proportional–integral–derivative (PID) control system is a simple, practical, highly effective method used to control the angular rotational velocity of electric motors. This paper describes the optimization of the PID control of a brushed DC motor (BDCM) with an embedded low-cost magnetic quadrature encoder. This paper demonstrates empirically that the feedback provided by low-cost magnetic encoders produces some inaccuracies and control artifacts that are not usually considered in simulations, proposing a practical optimization approach in order to improve the step overshoot and undershoot controller response. This optimization approach is responsible for the motion performances of a human-sized omnidirectional mobile robot using three motorized omnidirectional wheels.

Navigating between the different floors of a multistory building is a task that requires walking up or down stairs or taking an elevator or lift. This work proposes a procedure to take a remotely controlled elevator with an autonomous mobile robot based on 2D LIDAR. The application of the procedure requires ICP matching for mobile robot self-localization, a building with remotely controlled elevators, and a 2D map of the floors of the building detailing the position of the elevators. The results show that the application of the procedure enables an autonomous mobile robot to take a remotely controlled elevator and to navigate between floors based on 2D LIDAR information.

Omnidirectionality is a feature that allows motion in any direction without orientation maneuvers. Omnidirectional mobile robots are usually based on omni or mecanum wheels. The motion of an omnidirectional mobile robot is defined by a target motion command M=v,α,ω, where v is the module of the translational velocity; α is the angular orientation of the translational velocity, and ω is the angular velocity of the mobile robot. The motion is achieved by converting the target motion command into the target angular velocities that must be applied to the active wheels of the robot. This work proposes a simplified phasor-like interpretation of the relationship between the parameters of a specific motion command and the angular velocities of the wheels. The concept of phasor-like notation is validated from the analysis of the kinematics of omnidirectional mobile robots using omni wheels and mecanum wheels. This simplified phasor-like notation fosters unconstrained conceptual design of single-type and hybrid multi-wheeled omnidirectional mobile robots without the distribution or type of wheels being a design constraint.

This work proposes an Internet-of-Things (IoT) device for remote elevator control. The new contribution of this proposal to the state-of-the-art is that it can convert a manually operated elevator into a remote controlled elevator without requiring any intrusive manipulation or wiring connection in the elevator. This IoT device has been designed as an add-on non-contact tool which is placed over the original elevator button panel, using servomotors to press the original buttons. This design allows its fast deployment as a remote control tool that increases elevator accessibility through the use of messages, a webpage or a QR code. Some application examples of this proposal are non-contact use of elevators in pandemic conditions, and the unsupervised use of elevators by autonomous cleaning or delivery mobile robots. The experimental evaluation of the IoT device in real operational conditions has validated its non-contact control features.