Maria Prandini

Bio: Maria Prandini is an academic researcher from Polytechnic University of Milan. The author has contributed to research in topics: Probabilistic logic & Optimization problem. The author has an hindex of 29, co-authored 212 publications receiving 4032 citations. Previous affiliations of Maria Prandini include University of Oxford & Brescia University.

A probabilistic approach to aircraft conflict detection

Abstract: Conflict detection and resolution schemes operating at the mid-range and short-range level of the air traffic management process are discussed. Probabilistic models for predicting the aircraft position in the near-term and mid-term future are developed. Based on the mid-term prediction model, the maximum instantaneous probability of conflict is proposed as a criticality measure for two aircraft encounters. Randomized algorithms are introduced to efficiently estimate this measure of criticality and provide quantitative bounds on the level of approximation introduced. For short-term detection, approximate closed-form analytical expressions for the probability of conflict are obtained, using the short-term prediction model. Based on these expressions, an algorithm for decentralized conflict detection and resolution that generalizes potential fields methods for path planning to a probabilistic dynamic environment is proposed. The algorithms are validated using Monte Carlo simulations.

Optimal coordinated maneuvers for three dimensional aircraft conflict resolution

Abstract: In this paper, we study the problem of designing optimal coordinated maneuvers for multiple aircraft conflict resolution. We propose an energy function to select among all the conflict-free maneuvers the optimal one. The introduced cost function incorporates a priority mechanism that favors those maneuvers where aircraft with lower priority assume more responsibility in resolving the predicted conflicts. The energy-minimizing resolution maneuvers may involve changes of heading and speed, as well as of altitude. However, vertical maneuvers are penalized with respect to horizontal ones for the sake of passenger comfort. A geometric construction and a numerical algorithm for computing the optimal resolution maneuvers are given in the two aircraft case. As for the multiaircraft case, an approximation scheme is proposed to compute a suboptimal two-legged solution. Extensive examples are presented to illustrate the effectiveness of the proposed algorithms.

Pattern Recognition and Machine Learning

Abstract: Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

Consensus and Cooperation in Networked Multi-Agent Systems

Abstract: This paper provides a theoretical framework for analysis of consensus algorithms for multi-agent networked systems with an emphasis on the role of directed information flow, robustness to changes in network topology due to link/node failures, time-delays, and performance guarantees. An overview of basic concepts of information consensus in networks and methods of convergence and performance analysis for the algorithms are provided. Our analysis framework is based on tools from matrix theory, algebraic graph theory, and control theory. We discuss the connections between consensus problems in networked dynamic systems and diverse applications including synchronization of coupled oscillators, flocking, formation control, fast consensus in small-world networks, Markov processes and gossip-based algorithms, load balancing in networks, rendezvous in space, distributed sensor fusion in sensor networks, and belief propagation. We establish direct connections between spectral and structural properties of complex networks and the speed of information diffusion of consensus algorithms. A brief introduction is provided on networked systems with nonlocal information flow that are considerably faster than distributed systems with lattice-type nearest neighbor interactions. Simulation results are presented that demonstrate the role of small-world effects on the speed of consensus algorithms and cooperative control of multivehicle formations

An Overview of Recent Progress in the Study of Distributed Multi-Agent Coordination

Abstract: This paper reviews some main results and progress in distributed multi-agent coordination, focusing on papers published in major control systems and robotics journals since 2006. Distributed coordination of multiple vehicles, including unmanned aerial vehicles, unmanned ground vehicles, and unmanned underwater vehicles, has been a very active research subject studied extensively by the systems and control community. The recent results in this area are categorized into several directions, such as consensus, formation control, optimization, and estimation. After the review, a short discussion section is included to summarize the existing research and to propose several promising research directions along with some open problems that are deemed important for further investigations.