@article {3701, title = {Distributed model predictive control for energy management in a network of microgrids using the dual decomposition method}, journal = {Optimal Control Applications and Methods}, year = {2020}, chapter = {1-17}, abstract = {

Summary This paper deals with the application of model predictive control (MPC) to optimize power flows in a network of interconnected microgrids (MGs). More specifically, a distributed MPC (DMPC) approach is used to compute for each MG how much active power should be exchanged with other MGs and with the outer power grid. Due to the presence of coupled variables, the DMPC approach must be used in a suitable way to guarantee the feasibility of the consensus procedure among the MGs. For this purpose, we adopt a tailored dual decomposition method that allows us to reach a feasible solution while guaranteeing the privacy of single MGs (ie, without having to share private information like the amount of generated energy or locally consumed energy). Simulation results demonstrate the features of the proposed cooperative control strategy and the obtained benefits with respect to other classical centralized control methods.

}, keywords = {distributed systems, dual decomposition, microgrids, model predictive control}, doi = {10.1002/oca.2504}, url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/oca.2504}, author = {M. Razzanelli and E. Crisostomi and L. Pallottino and G. Pannocchia} } @article {3700, title = {Deconfliction of Motion Paths With Traffic Inspired Rules}, journal = {IEEE Robotics and Automation Letters}, volume = {4}, year = {2019}, month = {April}, pages = {2227-2234}, keywords = {Automobiles, Autonomous Vehicles, Collision Avoidance, multi-robot systems, Navigation, Physical Human-Robot Interaction, Roads, Robots, Safety}, issn = {2377-3766}, doi = {10.1109/LRA.2019.2899932}, author = {F. Celi and L. Wang and L. Pallottino and M. Egerstedt} } @conference {3382, title = {Design of an indoor autonomous robot navigation system for unknown environments}, booktitle = {International Conference on Modelling and Simulation for Autonomous Systems}, volume = {10756 LNCS Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in }, year = {2018}, note = {

Cited By :1

}, pages = {153-169}, doi = {10.1007/978-3-319-76072-8_11}, author = {L. Silvestri and L. Pallottino and S. Nardi} } @conference {3141, title = {Distributed Task-priority Based Control in Area Coverage \& Adaptive Sampling}, booktitle = {MTS/IEEE Oceans 2017}, year = {2017}, publisher = {IEEE}, organization = {IEEE}, address = {Aberdeen, Scotland, June 2017}, abstract = {

The paper presents the first simulative results and algorithmic developments of the task-priority based control applied to a distributed sampling network in an area coverage or adaptive sampling mission scenario. The proposed approach allowing the fulfilment of a chain of tasks with decreasing priority each of which directly related to both operability and safety aspects of the entire mission. The task-priority control is presented both in the centralized and decentralized implementations showing a comparison of performance. Finally simulations of the area coverage mission scenario are provided showing the effectiveness of the proposed approach.

}, keywords = {Robotics}, author = {T. Fabbri and E. Simetti and G. Casalino and L. Pallottino and A. Caiti} } @article {2473, title = {Distributed motion misbehavior detection in teams of heterogeneous aerial robots}, journal = {Robotics and Autonomous Systems information}, volume = {74 part A}, year = {2015}, month = {12/2015}, pages = {30-39}, abstract = {

This paper addresses the problem of detecting possible misbehavior in a group of autonomous mobile robots, which coexist in a shared environment and interact with each other and coordinate according to a set of common\ interaction rules. Such rules specify what actions each robot is allowed to perform in order to interact with the other members of the group. The rules are distributed, i.e., they can be evaluated only starting from the knowledge of the individual robot and the information the robot gathers from neighboring robots. We consider\ misbehaving\ those robots which, because of either spontaneous failures or malicious tampering, do not follow the rules and whose behavior thus deviates from the nominal assigned one. The main contribution of the paper is to provide a methodology to detect such misbehavior by observing the congruence of actual behavior with the assigned rules as applied to the actual state of the system. The presented methodology is based on a consensus protocol on the events observed by robots. The methodology is fully distributed in the sense that it can be performed by individual robots based only on the local available information, it has been theoretically proven and validated with experiments involving real aerial heterogeneous robots.

}, keywords = {Embedded Control, Robotics}, doi = {10.1016/j.robot.2015.06.008}, url = {http://www.sciencedirect.com/science/article/pii/S0921889015001360}, author = {S. Martini and D. Di Baccio and F. Alarc{\`o}n-Romero and A. Viguria-Jim{\'e}nez and L. Pallottino and G. Dini and A. Ollero} } @conference {1702, title = {Distributed Multi{\textendash}level Motion Planning for Autonomous Vehicles in Large Scale Industrial Environments}, booktitle = {IEEE International Conference on Emerging Technologies \& Factory Automation (ETFA)}, year = {2013}, month = {09/2013}, pages = {1-8}, abstract = {

In this paper we propose a distributed coordination algorithm for safe and efficient traffic management of heterogeneous robotic agents, moving within dynamic large scale industrial environments. The algorithm consists of a distributed resource{\textendash}sharing protocol involving a re{\textendash}planning strategy. Once every agent is assigned with a desired motion path, the algorithm ensures ordered traffic flows of agents, that avoid inter{\textendash}robot collision and system deadlock (stalls). The algorithm allows multi{\textendash}level representation of the environment, i.e. large or complex rooms may be seen as a unique resource with given capacity at convenience, which makes the approach appealing for complex industrial environments. Under a suitable condition on the maximum number of agents with respect to the capacity of the environment, we prove that the algorithm correctly allows mutual access to shared resources while avoiding deadlocks. The proposed solution requires no centralized mechanism, no shared memory or ground infrastructure support. Only a local inter{\textendash}robot communication is required, i.e. every agent must communicate with a limited number of other spatially adjacent robots. We finally show the effectiveness of the proposed approach by simulations, with application to an industrial scenario.

}, keywords = {Robotics}, doi = {10.1109/ETFA.2013.6647973 }, author = {L. Cancemi and A. Fagiolini and L. Pallottino} } @conference {MFP11, title = {Decentralized Coordination System for Multiple AGVs in a Structured Environment}, booktitle = {2011 Congress of the International Federation of Automatic Control}, year = {2011}, month = {Aug 28 - Sept 1}, pages = {6005 - 6010}, address = {Milano, italy}, keywords = {Embedded Control, Robotics}, author = {S. Manca and A. Fagiolini and L. Pallottino} } @article {PSFB06-TRO, title = {Decentralized cooperative policy for conflict resolution in multi-vehicle systems}, journal = {IEEE Trans. on Robotics}, volume = {23}, number = {6}, year = {2007}, pages = {1170-1183}, abstract = {

In this paper we propose a novel policy for steering multiple vehicles between assigned independent start and goal configurations and ensuring collision avoidance. The policy rests on the assumption that agents are all cooperating by implementing the same traffic rules. However, the policy is completely decentralized, as each agent decides its own motion by applying those rules only on locally available information, and totally scalable, in the sense that the amount of information processed by each agent and the computational complexity of the algorithms are not increasing with the number of agents in the scenario. The proposed policy applies to systems in which new vehicle may enter the scene and start interacting with existing ones at any time, while others may leave. Under mild conditions on the initial configurations, the policy is shown to be safe, i.e. to guarantee collision avoidance throughout the system evolution. In the paper, conditions are discussed on the desired configurations of agents under which the ultimate convergence of all vehicles to their goals can also be guaranteed. To show that such conditions are actually necessary and sufficient, which turns out to be a challenging liveness verification problem for a complex hybrid automaton, we employ a probabilistic verification method. The paper finally reports on simulations for systems of several tens of vehicles, and with some experimental implementation showing the practicality of the approach.

}, keywords = {Embedded Control, Robotics}, author = {L. Pallottino and V. G. Scordio and E. Frazzoli and A. Bicchi} } @conference {FVPDB:CDC07, title = {Decentralized Intrusion Detection for Secure Cooperative Multi-Agent Systems}, booktitle = {Proc. IEEE Int. Conf. on Decision and Control}, year = {2007}, pages = {1553-1558}, abstract = {

In this paper we address the problem of detecting faulty behaviors of cooperative mobile agents. A novel decentralized and scalable architecture that can be adopted to realize a monitor of the agents

}, keywords = {Embedded Control, Robotics}, author = {A. Fagiolini and G. Valenti and L. Pallottino and G. Dini and A. Bicchi} } @booklet {FPD{\textquoteright}07, title = {Decentralized Intrusion Detection in Cooperative Multi-Agent Systems}, year = {2007}, note = {

Poster Presentation

}, month = {April}, abstract = {

We address the problem of detecting faulty behaviors of robots belonging to a multi-agent system. Our objective is to develop a scalable architecture that can be adopted to realize a completely decentralized intrusion detector monitoring the agents{\textquoteright} behavior. We want the solution to be independent from the set of {\textquoteleft}{\textquoteleft}rules{\textquoteright}{\textquoteright} describing the interaction among the agents, and from their dynamics; (non-invasive) mainly based on HW/SW components that are already present on-board of each agent. We focus on systems with decentralized cooperation schemes where cooperation is obtained by sharing a set of {\textquoteleft}{\textquoteleft}rules{\textquoteright}{\textquoteright} by which each agent plans its next {\textquoteleft}{\textquoteleft}action{\textquoteright}{\textquoteright} and where some of the agents may act not according to the rules due to spontaneous failure, tampering, or malicious introduction.

}, keywords = {Embedded Control, Robotics}, author = {A. Fagiolini and L. Pallottino and G. Dini} } @conference {PB06, title = {A Dynamic Programming Approach to Optimal Planning for Vehicles with Trailers}, booktitle = {Proc. IEEE Int. Conf. on Robotics and Automation}, year = {2007}, pages = {3098 - 3103}, abstract = {

In this paper we deal with the optimal feedback synthesis problem for robotic vehicles with trailers which can be modeled by differential equations in chained-form. With respect to classical methods for numerical evolution of optimal feedback synthesis via Dynamic Programming which are based on both input and state discretization, our method exploits the lattice structure naturally imposed on the reachable set by input quantization. A generalized Dijkstra algorithm can be used to obtain optimal feedback control laws, for chained-form vehicles with n-trailers, in an effective way.

}, keywords = {Embedded Control, Robotics}, author = {L. Pallottino and A. Bicchi} } @conference {PSFB-MTNS06, title = {Decentralized and scalable conflict resolution strategy for multi-agents systems}, booktitle = {Int. Symp. on Mathematical Theory of Networks and Systems}, year = {2006}, abstract = {

A decentralized cooperative collision avoidance control policy for planar vehicle recently proposed is herein considered. Given some simple conditions on initial configurations of agents, the policy is known to ensure safety (i.e., collision avoidance) for an arbitrarily large number of vehicles. The method is highly scalable, and effective solutions can be obtained for several tens of autonomous agents. On the other hand, the liveness property of the policy, i.e. the capability of negotiating a solution in finite time, is not yet completely understood. First a 3D workspace extension is proposed. Furthermore, based on a condition on target configuration previously proposed, some general results on the liveness property are reported. Finally, qualitative evaluations on the strategy and on the proposed target sparsity condition are pointed out.

}, keywords = {Embedded Control, Robotics}, author = {L. Pallottino and V. G. Scordio and E. Frazzoli and A. Bicchi} } @conference {PSFB05, title = {Decentralized Cooperative Conflict Resolution for Multiple Nonholonomic Vehicles}, booktitle = {Proc. AIAA COnf. on Guidance, Navigation and Control}, year = {2005}, abstract = {

In this paper, we consider the problem of collision-free motion planning for multiple nonholonomic planar vehicles. Each vehicle is capable of moving at constant speed along paths with bounded curvature, and is aware of the position and heading of other vehicles within a certain sensing radius. No other information exchange is required between vehicles. We propose a spatially decentralized, cooperative hybrid control policy that ensures safety for arbitrary numbers of vehicles. Furthermore, we show that under certain conditions, the policy avoids dead- and livelock, and eventually all vehicles reach their intended targets. Simulations and experimental results are presented and discussed.

}, keywords = {Embedded Control, Robotics}, author = {L. Pallottino and V. G. Scordio and E. Frazzoli and A. Bicchi} } @conference {PSB04, title = {Decentralized Cooperative Conflict Resolution Among Multiple Autonomous Mobile Agents}, booktitle = {cdc}, year = {2004}, pages = {4758-4763}, abstract = {

In this paper we consider policies for cooperative, decentralized traffic management among a number of autonomous mobile agents. The conflict resolution problem is addressed considering realistic restrictions on possible maneuvers. We formulate this problem as one in Mixed Integer Linear Programming (MILP). The method, which proves successful in a centralized implementation with a large number of cooperating agents, is also extended to a decentralized setting. Conditions for the existence of conflict avoidance maneuvers for a system of 5 autonomous agents with a transitive information structure are provided, along with the explicit policy to be applied by each agent.

}, keywords = {Embedded Control, Robotics}, author = {L. Pallottino and V. G. Scordio and A. Bicchi} }