This paper describes a simultaneous localization and mapping (SLAM) algorithm for use in unstructured environments that is effective regardless of the geometric complexity of the environment. Features are described using B-splines as modeling tool, and the set of control points defining their shape is used to form a complete and compact description of the environment, thus making it feasible to use an extended Kalman-filter (EKF) based SLAM algorithm. This method is the first known EKF-SLAM implementation capable of describing general free-form features in a parametric manner. Efficient strategies for computing the relevant Jacobians, perform data association, initialization, and map enlargement are presented. The algorithms are evaluated for accuracy and consistency using computer simulations, and for effectiveness using experimental data gathered from different real environments.

This article analyses three of the Sustainable Development Goals (SDGs) gathered by the 2030 Agenda and adopted by the United Nations, and how online educational models may help to reach these goals. Specifically, the three goals discussed through this article are: (i) Ensure inclusive and equitable quality education and promote lifelong learning opportunities for all (Goal 4); (ii) reduce inequality within and among countries (Goal 10); and (iii) take urgent action to combat climate change and its impacts (Goal 13). This work delves fundamentally into aspects related to online engineering education, such as the impact of the carbon footprint in online education, the reduction of geographical barriers and the social gap, and the complete online accessibility to the educational environment. Finally, this article presents the case of the International University of La Rioja with its 100% online methodology, and approximately 42,000 students distributed throughout the world. This institution is supported by tools that facilitate engineering training for people with reduced mobility and who are geographically dispersed, reducing the carbon footprint through remote training.

The prospect of using humanoid robots in practical applications attracts an important research effort and the latest steps forward in robot technology show many remarkable achievements where design aspects, control systems and software evolution regarding humanoid machines have been realised. While aiming to improve humanoid robots' overall performance, it is required that they could work for a long time spending minimum energy without losing their kinematic skills. In this direction, a new kind of non‐linear actuator, SMART, based on quasi‐resonance principle, has been developed by the Industrial Automation Institute to improve the overall performance of biped locomotion.