Novel Biological Based Method for Robot Navigation and Localization

The capability and reliability are crucial characteristics of mobile robots while navigating in complex environments. These robots are expected to perform many useful tasks which can improve the quality of life greatly. Robot localization and decisionmaking are the most important cognitive processes during navigation. However, most of these algorithms are not efficient and are challenging tasks while robots navigate through complex environments. In this paper,we propose a biologically inspired method for robot decision-making, based on rat’s brain signals. Rodents accurately and rapidly navigate in complex spaces by localizing themselves in reference to the surrounding environmental landmarks. Firstly, we analyzed the rats’ strategies while navigating in the complex Y-maze, and recorded local field potentials(LFPs), simultaneously.The recorded LFPs were processed and different features were extracted which were used as the input in the artificial neural network(ANN) to predict the rat’s decision-making in each junction. The ANN performance was tested in a real robot and good performance is achieved. The implementation of our method on a real robot, demonstrates its abilities to imitate the rat’s decision-making and integrate the internal states with external sensors, in order to perform reliable navigation in complex maze.

Applications of Carbon Nanotubes in the Internet of Things Era

The post-Moore's era has boosted the progress in carbon nanotube-based transistors.Indeed,the 5 G communication and cloud computing stimulate the research in applications of carbon nanotubes in electronic devices.In this perspective,we deliver the readers with the latest trends in carbon nanotube research,including high-frequency transistors,biomedical sensors and actuators,brain–machine interfaces,and flexible logic devices and energy storages.Future opportunities are given for calling on scientists and engineers into the emerging topics.