Abstract
The localization algorithms have different errors which can impair the robot's navigation. In this way, we propose an approach that will supervise the localization while the robot navigate. Our approach is based on another work present in the literature, where we detected a problem during its analysis. Therefore, this article will present a new method based on the RLS algorithm, to solve the identified problem. Besides, we propose the supervision of two more localization algorithms, being now four the supervised algorithms, namely: Augmented Monte Carlo Localization, Extended Kalman Filter with Beacons, Perfect Match and Odometry. The results show that the robustness and reliability of the system were increased.

Abstract

Abstract

Abstract
The following topics are dealt with: mobile robots; multi-robot systems; path planning; robot vision; service robots; collision avoidance; learning (artificial intelligence); legged locomotion; control engineering computing; production engineering computing.

Abstract
This work presents a novel methodology for Sub-Optimal Excitation Signal Generation and Optimal Parameter Estimation of constrained nonlinear systems. It is proposed that the evaluation of each signal must also account for the difference between real and estimated system parameters. However, this metric is not directly obtained once the real parameter values are not known. The alternative presented here is to adopt the hypothesis that, if a system can be approximated by a white box model, this model can be used as a benchmark to indicate the impact of a signal over the parametric estimation. In this way, the proposed method uses a dual layer optimization methodology: (i) Inner Level; For a given excitation signal a nonlinear optimization method searches for the optimal set of parameters that minimizes the error between the outputs of the optimized and benchmark models. (ii) At the outer level, a metaheuristic optimization method is responsible for constructing the best excitation signal, considering the fitness coming from the inner level, the quadratic difference between its parameters and the cost related to the time and space required to execute the experiment.

Abstract
Automobile industry faces one of the most flexible productivity caused by the number of customized models variants due to the buyers needs. This fact requires the production system to introduce flexible, adaptable and cooperative with humans solutions. In the present work, a panel that should be mounted inside a van is addressed. For that purpose, a mobile manipulator is suggested that could share the same space with workers helping each other. This paper presents the navigation system for the robot that enters the van from the rear door after a ramp, operates and exits. The localization system is based on 3DOF methodologies that allow the robot to operate autonomously. Real tests scenarios prove the precision and repeatability of the navigation system outside, inside and during the ramp access of the van.