Mechatronic systems and their characteristics

This article presents a patented mechanical concept for controlling and leveling a conventional robot with four moving parts and the methods that led to the development of this mechatronic system. Shows excellent maneuverability and great advantages when moving in difficult conditions like a robot. The article discusses an improved approach to developing mechatronic systems that is well known. A sophisticated approach allows you to consciously plan and manage a process diagram

Mechatronics & the cloud

Conventionally, the engineering design process has assumed that the design team is able to exercise control over all elements of the design, either directly or indirectly in the case of sub-systems through their specifications. The introduction of Cyber-Physical Systems (CPS) and the Internet of Things (IoT) means that a design team’s ability to have control over all elements of a system is no longer the case, particularly as the actual system configuration may well be being dynamically reconfigured in real-time according to user (and vendor) context and need. Additionally, the integration of the Internet of Things with elements of Big Data means that information becomes a commodity to be autonomously traded by and between systems, again according to context and need, all of which has implications for the privacy of system users. The paper therefore considers the relationship between mechatronics and cloud-basedtechnologies in relation to issues such as the distribution of functionality and user privacy

PIN generation using EEG : a stability study

In a previous study, it has been shown that brain activity, i.e. electroencephalogram (EEG) signals, can be used to generate personal identification number (PIN). The method was based on brain–computer interface (BCI) technology using a P300-based BCI approach and showed that a single-channel EEG was sufficient to generate PIN without any error for three subjects. The advantage of this method is obviously its better fraud resistance compared to conventional methods of PIN generation such as entering the numbers using a keypad. Here, we investigate the stability of these EEG signals when used with a neural network classifier, i.e. to investigate the changes in the performance of the method over time. Our results, based on recording conducted over a period of three months, indicate that a single channel is no longer sufficient and a multiple electrode configuration is necessary to maintain acceptable performances. Alternatively, a recording session to retrain the neural network classifier can be conducted on shorter intervals, though practically this might not be viable

Vision-based landing of a simulated unmanned aerial vehicle with fast reinforcement learning

Landing is one of the difficult challenges for an unmanned aerial vehicle (UAV). In this paper, we propose a vision-based landing approach for an autonomous UAV using reinforcement learning (RL). The autonomous UAV learns the landing skill from scratch by interacting with the environment. The reinforcement learning algorithm explored and extended in this study is Least-Squares Policy Iteration (LSPI) to gain a fast learning process and a smooth landing trajectory. The proposed approach has been tested with a simulated quadrocopter in an extended version of the USARSim Unified System for Automation and Robot Simulation) environment. Results showed that LSPI learned the landing skill very quickly, requiring less than 142 trials

The robot programming network

The Robot Programming Network (RPN) is an initiative for creating a network of robotics education laboratories with remote programming capabilities. It consists of both online open course materials and online servers that are ready to execute and test the programs written by remote students. Online materials include introductory course modules on robot programming, mobile robotics and humanoids, aimed to learn from basic concepts in science, technology, engineering, and mathematics (STEM) to more advanced programming skills. The students have access to the online server hosts, where they submit and run their programming code on the fly. The hosts run a variety of robot simulation environments, and access to real robots can also be granted, upon successful achievement of the course modules. The learning materials provide step-by-step guidance for solving problems with increasing level of dif- ficulty. Skill tests and challenges are given for checking the success, and online competitions are scheduled for additional motivation and fun. Use of standard robotics middleware (ROS) allows the system to be extended to a large number of robot platforms, and connected to other existing tele-laboratories for building a large social network for online teaching of robotics.Support of IEEE RAS through the CEMRA program (Creation of Educational Material for Robotics and Automation) is gratefully acknowledged. This paper describes research done at the Robotic Intelligence Laboratory. Support for this laboratory is provided in part by Ministerio de Economia y Competitividad (DPI2011-27846), by Generalitat Valenciana (PROMETEOII/2014/028) and by Universitat Jaume I (P1-1B2011-54)

Prototype development of graphical pattern security system on Raspberry Pi

Password is a primary security mechanism that consists of a secret phrase created using alphabetic, numeric, alphanumeric, and symbolic characters, or a combina-tion. It is used to restrict access to a system, application, or service to only those users who have the authorization to use the system or device. Because of in-creased computing power, modern passwords must be very long and complicat-ed, which will make them hard to remember. Some research studies show that it is easier for people to remember visual passwords instead of textual ones. There-fore, this research aims to enhance the authentication process's security using the graphical pattern unlock approach on Raspberry Pi. The grid size of 5×5 was se-lected in the implementation, as it provides the tradeoff between security strength and an easy pattern to remember. The proposed system could be connected to the smart home system, which can enhance their security. Prototype validation re-vealed that the prototype is working as intended, and the authentication process took around 1.2 seconds to complete

Acta Universitatis Sapientiae - Electrical and Mechanical Engineering

Series Electrical and Mechanical Engineering publishes original papers and surveys in various fields of Electrical and Mechanical Engineering

The challenges and opportunities of artificial intelligence in implementing trustworthy robotics and autonomous systems

Effective Robots and Autonomous Systems (RAS) must be trustworthy. Trust is essential in designing autonomous and semi-autonomous technologies, because “No trust, no use”. RAS should provide high quality of services, with the four key properties that make it trust, i.e. they must be (i) robust for any health issues, (ii) safe for any matters in their surrounding environments, (iii) secure for any threats from cyber spaces, and (iv) trusted for human-machine interaction. We have thoroughly analysed the challenges in implementing the trustworthy RAS in respects of the four properties, and addressed the power of AI in improving the trustworthiness of RAS. While we put our eyes on the benefits that AI brings to human, we should realise the potential risks that could be caused by AI. The new concept of human-centred AI will be the core in implementing the trustworthy RAS. This review could provide a brief reference for the research on AI for trustworthy RAS