Due to their capability of acquiring aerial imagery, camera-equipped Unmanned Aerial Vehicles (UAVs) are very cost-effective tools for acquiring traffic information. However, not enough attention has been given to the validation of the accuracy of these systems. In this paper, an analysis of the most significant sources of error is done. This includes three key components. First, a vehicle state estimation by means of statistical filtering. Second, a quantification of the most significant sources of error. Third, a benchmark of the estimated state compared with state-of-the-art reference sensors. This work presents ways to minimize the errors of the most relevant sources. With these error reductions, camera-equipped UAVs are very attractive tools for traffic data acquisition. The test data and the source code are made publicly available.

Autonomous driving is an important trend of the automotive industry. The continuous research towards this goal requires a precise reference vehicle state estimation under all circumstances in order to develop and test autonomous vehicle functions. However, even when lane-accurate positioning is expected from oncoming technologies, like the L5 GPS band, the question of accurate positioning in roofed areas, e.g., tunnels or park houses, still has to be addressed. In this paper, a novel procedure for a reference vehicle state estimation is presented. The procedure includes three main components. First, a robust standstill detection based purely on signals from an Inertial Measurement Unit. Second, a vehicle state estimation by means of statistical filtering. Third, a high accuracy LiDAR-based positioning method that delivers velocity, position and orientation correction data with a mean error of 0.1 m/s, 4.7 cm and 1° respectively. Runtime tests on a CPU indicates the possibility of real-time implementation.

Multiagent technology raised great expectations from the outset, and these expectations are still high today. A technology that allows the creation of systems that are autonomous, reactive, proactive, and have entities with social skills is necessarily very appealing. Many initiatives have emerged to develop the application of this technology in different areas, including manufacturing. Multiagent-based solutions typically use this technology to create distributed systems with decentralized decision making as a way to tackle complex systems or problems by dividing the complexity among agents. Unfortunately, most works do not go further than the definition of agents or architectures, which prevents industry from adopting this technology. This paper presents an approach to implementing the shop floor control of an automated distribution center following a multiagent approach. This implementation divides the system into agents in charge of the management of the system while highlighting the communication channels with shop floor control equipment.

Tracking persons in dangerous situations as well as monitoring their physical condition, is often crucial for their safety. The systems commonly used for this purpose do not include individual monitoring or are too expensive and intrusive to be deployed in common situations. In this project, a mobile system based on energy-efficient wireless sensor networks (WSNs) and active radio frequency identification (RFID) has been developed to achieve ubiquitous positioning and monitoring of people in hazardous situations. The system designed can identify each individual, locate him/her, send data regarding their physical situation, and ascertain whether they are located in a confined space. A new algorithm called time division double beacon scheduling (TDDBS) has been implemented to increase operation time and data transmission rate of the nodes in the system. The results show that the use of this system allows us to find the location and state of a person, as well as to provide an analysis of the potential risks at each moment, in real time and in an energy-efficient way. In an emergency, the system also allows for quicker intervention, as it not only provides the location and causes of the event, but also informs about the physical condition of the individual at that moment.

In order to improve the operations management of a distribution center, this paper proposes a management system based on Multi-Agent Systems (MAS) enhanced with Radio-Frequency Identification (RFID) or RFIDIMSII. An experimental platform composed of a simulation combined with a physical platform is used to study a company situated in Spain. It has been necessary because of the company’s complexity. The simulation software WITNESS has been used to study different scenarios. It leads to control the main parameters of the company, for example the schedule of orders. It has been demonstrated that the RFID-IMSII system improves the system utilized by the company.

Recent research on highly distributed control methods for complex systems has produced a series of new philosophies based on negotiation which bring together process engineering with computer science. Among these control philosophies the ones based on multi-agent systems (MAS) have become especially relevant. However these MAS models have the drawback of an excessive dependence on up-to-date information about the products and other elements that move within the system. However a new technology has come out that can help solve this problem: radio-frequency identification enhanced information management systems (RFID-IMS). RFID-IMS technology is being rapidly introduced in industry mainly for logistic purposes. But, once these systems are in place, manufacturing can benefit so deeply that MAS is likely to become a realistic solution to highly increase flexibility and capacity in manufacturing environments. Solution that can now be dubbed as: RFID-enhanced intelligent manufacturing systems (RFID-IMS II).

This article describes a new control scheme designed for a three-degree-of-freedom flexible arm. This arm has been built with light links, has most of its mass concentrated at the tip, and uses a special mechanical configuration to approximately decouple tip motions in spherical coordinates. This configuration facilitates the dynamic modeling and control of the arm. A compliance matrix can be used to model the oscillations of the structure. A consequence of this simple dynamic is that minimum sensing effort is required (only direct motor and tip measurements), and the use of complex observers is avoided because the state of the system can be very easily obtained from these measurements. A two-nested control-loop scheme is used to control the tip position by using joint position and tip acceleration feedbacks. The stability of the controlled system is analytically proven in the case of perfect dynamic modeling. Then, an analysis of stability in the case of modeling errors is carried out, and conditions for local stability are derived. Experimental results are presented for the cases of perturbation control and trajectory tracking. Comparative results between controlled and noncontrolled tip responses are also shown.

This paper analyzes the possibility of carrying out the collision detection as a first step towards the position/force control of three-degree-of-freedom flexible arm by using gauges placed at some distance of the tip (where contact is expected) in such way that they can easily stand the impact. Simulated results over a prototype three-degree-of-freedom flexible arm are presented.