Andrea Bonci

A Bayesian approach to the Hough transform for line detection

This paper explains how to associate a rigorous probability value to the main straight line features extracted from a digital image. A Bayesian approach to the Hough Transform (HT) is considered. Under general conditions, it is shown that a probability measure is associated to each line extracted from the HT. The proposed method increments the HT accumulator in a probabilistic way: first calculating the uncertainty of each edge point in the image and then using a Bayesian probabilistic scheme for fusing the probability of each edge point and calculating the line feature probability.

A scalable production efficiency tool for the robotic cloud in the fractal factory

The present paper proposes an effective metrics for production efficiency and a bottleneck detection algorithm of recursive nature for its application on lightweight embedded systems on board of the robotics and automation components of the factory of the future. The proposed methodology is particularly suited if the fractal paradigm is applied to the factory seen as a complex system of systems but with relevant self-similarities across the several layers of components and structures from the shop-floor up to the enterprise level. A performance test has been conducted to demonstrate the viability of the technology for tiny embedded devices with the use of declarative embedded database language. Due to the high scalability of the algorithm and its simplicity, it seems suitable also for the robotic cloud paradigm, where constituent mechatronics, sensors and actuators components are provided as a service. The results provided suggests that, with the use of similar recursive and distributed form of computing, production bottlenecks or fault detection can be scaled to address the complex and pervasive cyber-physical systems problems that characterize the 4th industrial revolution strategies.

A motorcycle enhanced model for active safety devices in intelligent transport systems

This paper proposes to enhance an existing motorcycle dynamics model, in order to take account of the longitudinal dynamics, the wheels dynamics and the rear wheel traction. The added equations of motion are obtained using Lagrangian formulation. Also, to model the road surface, two additional equations describing the longitudinal slip and the longitudinal forces dynamic are included. The model is able to describe the coupling of the in-plane (longitudinal) and out-of-plane (lateral) dynamics and represents a suitable computational tool for designing preventive motorcycle active safety systems and controller synthesis applications. Simulation results and discussions are given in order to illustrate the effectiveness of the proposed mathematical tool.

Sonar and Video Data Fusion for Robot Localization and Environment Feature Estimation

In this paper the localization and environment feature estimation problems are formulated in a stochastic setting, and an Extended Kalman Filtering (EKF) approach is proposed for the integration of odometric, video camera and sonar measures. The environment is supposed to be only partially known, and a probabilistic method for sensory data fusion aimed at increasing the environment knowledge is considered.

Motorcycle's lateral stability issues: Comparison of methods for dynamic modelling of roll angle

This paper proposes a simulation scenario in order to compare a proposed model of a motorcycle in cornering condition. The behaviours obtained by considering a linearized roll dynamic and a nonlinear roll dynamic have been investigated in order to evaluate their use in designing automatic stability controls of a motorcycle. The former model shows a linear dependency on the roll angle and the steer angle. The second model starts from the former and removes the roll angle linearization. The comparative analysis of the results shows how the linearized model is able to describe adequately the cornering dynamics for sufficiently large values of roll angle. These performances are suitable for designing a motorcycle active safety device controlling the lateral dynamics for preventing lateral falls.

Motorcycle lateral and longitudinal dynamic modeling in presence of tyre slip and rear traction

This paper proposes a mathematical model of a motorcycle that deals with the lateral and longitudinal dynamics, the tyre slip and the rear wheel traction. The vehicle is considered as an assembly of two rigid bodies. The proposed dynamic formulation is based on Lagranges equations, it allows to formulate the equations of motion with 7 degrees of freedom (DoF). The model assess the vehicle behavior in response to a propulsion torque applied to the rear wheel and a rider torque applied to the motorcycle handlebar. The model is able to describe the coupling of the in-plane (longitudinal) and out-of-plane (lateral) dynamics taking into account the rear and the front longitudinal tyre slip related to the rear wheel traction. In order to solve the linearized equations of motion, no multibody software was used, only numeric simulation tools such as MATLAB.

Data Fusion for Visual and Ultrasonic Map-Building

Abstract The paper presents a method for integrating ultrasonic range readings and monocular visual information in the environmental occupancy grid of an autonomous vehicle. A simple visual interpretation of ultrasonic range data stored in an occupancy grid map is considered. This environment representation is fused at the feature level of interpretation with the monocular vision information in order to validate and to update the occupancy grid map. The main features of the proposed method are the low computational efforts and the low cost of the sensor systems.

Information Management and Decision Making Supported by an Intelligence System in Kitchen Fronts Control Process

Measuring systems used for alternative control are the basis of the kitchen fronts acceptance. The assessment of such products is difficult. On the basis of the performed analysis, it can be said that different operators make different decisions that result in different problems in a case study manufacturing company. In the work, the authors propose a cyber-physical distributed computing infrastructure to implement performance metrics methods extended to manage the control system and to support the decisions concerning improvements in the control process. It will result in the minimization or avoidance of operators’ mistakes concerning the wrong acceptance or rejection of the finished product.

Video data validation by sonar measures for robot localization and environment feature estimation

In this paper, the robust robot localization problem with respect to uncertainties on environment features is formulated in a stochastic setting, and an extended Kalman filtering approach is proposed for the integration of odometric, video camera, and sonar measures. The environment is supposed to be only partially known, and a probabilistic method for sensor data fusion aimed at increasing the environment knowledge is considered.

A Database-Centric Framework for the Modeling, Simulation, and Control of Cyber-Physical Systems in the Factory of the Future

Abstract The factory of the future scenario asks for new approaches to cope with the incoming challenges and complexity of cyber-physical systems. The role of database management systems is becoming central for control and automation technology in this new industrial scenario. This article proposes database-centric technology and architecture that aims to seamlessly integrate networking, artificial intelligence, and real-time control issues into a unified model of computing. The proposed methodology is also viable for the development of a framework that features simulation and rapid prototyping tools for smart and advanced industrial automation. The full expression of the potentialities in the presented approach is expected in particular for applications where tiny and distributed embedded devices collaborate to a shared computing task of relevant complexity.