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A Q-learning based multi-strategy integrated artificial bee colony algorithm with application in unmanned vehicle path planning

Ni, Xinrui (author), Hu, Wei (author), Fan, Q. (author), Cui, Yibing (author), Qi, Chongkai (author)

Artificial bee colony (ABC) is a prominent algorithm that offers great exploration capabilities among various meta-heuristic algorithms. However, its monotonous and one-dimensional search strategy limits its searching performance in the solving process. Thus, to address this issue, a Q-learning based multi-strategy integrated ABC algorithm ...

journal article 2024

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Hierarchical Motion Planning and Tracking for Autonomous Vehicles Using Global Heuristic Based Potential Field and Reinforcement Learning Based Predictive Control

Du, Guodong (author), Zou, Yuan (author), Zhang, Xudong (author), Li, Z. (author), Liu, Qi (author)

The autonomous vehicle is widely applied in various ground operations, in which motion planning and tracking control are becoming the key technologies to achieve autonomous driving. In order to further improve the performance of motion planning and tracking control, an efficient hierarchical framework containing motion planning and tracking...

journal article 2023

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Optimal Selection and Tracking of Generalized Nash Equilibria in Monotone Games

Benenati, E. (author), Ananduta, W. (author), Grammatico, S. (author)

A fundamental open problem in monotone game theory is the computation of a specific generalized Nash equilibrium (GNE) among all the available ones, e.g. the optimal equilibrium with respect to a system-level objective. The existing GNE seeking algorithms have in fact convergence guarantees toward an arbitrary, possibly inefficient,...

journal article 2023

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Controller Placement with Respect to Controller Reachability

Xu, Ran (author), Wang, F. (author), Kooij, Robert (author)

In this paper we investigate the controller placement problem on networks using controller reachability as the network performance metric. This metric is defined as the probability that each node can reach at least one controller, given that each link is operational with a fixed probability. By exploring placements for more than 100 real-world...

conference paper 2023

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Group-Based Distributed Auction Algorithms for Multi-Robot Task Assignment

Bai, X. (author), Fielbaum, Andres (author), Kronmüller, M. (author), Knödler, L. (author), Alonso-Mora, J. (author)

This paper studies the multi-robot task assignment problem in which a fleet of dispersed robots needs to efficiently transport a set of dynamically appearing packages from their initial locations to corresponding destinations within prescribed time-windows. Each robot can carry multiple packages simultaneously within its capacity. Given a...

journal article 2023

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A Scalable Distributed Dynamical Systems Approach to Learn the Strongly Connected Components and Diameter of Networks

Reed, Emily A. (author), Ramos, Guilherme (author), Bogdan, Paul (author), Gonçalves Melo Pequito, S.D. (author)

Finding strongly connected components (SCCs) and the diameter of a directed network play a key role in a variety of machine learning and control theory problems. In this article, we provide for the first time a scalable distributed solution for these two problems by leveraging dynamical consensus-like protocols to find the SCCs. The proposed...

journal article 2023

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Adaptive Composite Online Optimization: Predictions in Static and Dynamic Environments

Zattoni Scroccaro, P. (author), Sharifi K., Arman (author), Mohajerin Esfahani, P. (author)

In the past few years, online convex optimization (OCO) has received notable attention in the control literature thanks to its flexible real-time nature and powerful performance guarantees. In this article, we propose new step-size rules and OCO algorithms that simultaneously exploit gradient predictions, function predictions and dynamics,...

journal article 2023

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Topological-Graph Dependencies and Scaling Properties of a Heuristic Qubit-Assignment Algorithm

Steinberg, M.A. (author), Feld, S. (author), Almudever, Carmen G. (author), Marthaler, Michael (author), Reiner, Jan Michael (author)

The qubit-mapping problem aims to assign and route qubits of a quantum circuit onto an noisy intermediate-scale quantum (NISQ) device in an optimized fashion, with respect to some cost function. Finding an optimal solution to this problem is known to scale exponentially in computational complexity; as such, it is imperative to investigate...

journal article 2022

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Distributed Time-Varying Optimization of Second-Order Multiagent Systems Under Limited Interaction Ranges

Hong, Huifen (author), Baldi, S. (author), Yu, Wenwu (author), Yu, Xinghuo (author)

This article investigates the distributed time-varying optimization problem for second-order multiagent systems (MASs) under limited interaction ranges. The goal is to seek the minimum of the sum of local time-varying cost functions (CFs), where each CF is only available to the corresponding agent. Limited communication range refers to the...

journal article 2022

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An MPC-Based Rescheduling Algorithm for Disruptions and Disturbances in Large-Scale Railway Networks

Cavone, Graziana (author), van den Boom, A.J.J. (author), Blenkers, Lex (author), Dotoli, Mariagrazia (author), Seatzu, Carla (author), De Schutter, B.H.K. (author)

Railways are a well-recognized sustainable transportation mode that helps to satisfy the continuously growing mobility demand. However, the management of railway traffic in large-scale networks is a challenging task, especially when both a major disruption and various disturbances occur simultaneously. We propose an automatic rescheduling...

journal article 2022

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Barrier Function-based Safe Reinforcement Learning for Formation Control of Mobile Robots

Zhang, Xinglong (author), Peng, Yaoqian (author), Pan, W. (author), Xu, Xin (author), Xie, Haibin (author)

Distributed model predictive control (DMPC) concerns how to online control multiple robotic systems with constraints effectively. However, the nonlinearity, nonconvexity, and strong interconnections of dynamic system models and constraints can make the real-time and real-world DMPC implementations nontrivial. Reinforcement learning (RL)...

conference paper 2022

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Free Energy Principle for State and Input Estimation of a Quadcopter Flying in Wind

Bos, F.R.R.C. (author), Anil Meera, A. (author), Benders, D. (author), Wisse, M. (author)

The free energy principle from neuroscience provides a brain-inspired perception scheme through a data-driven model learning algorithm called Dynamic Expectation Maximization (DEM). This paper aims at introducing an exper-imental design to provide the first experimental confirmation of the usefulness of DEM as a state and input estimator for...

conference paper 2022

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Excitation allocation for generic identifiability of linear dynamic networks with fixed modules

Dreef, H. J. (author), Shi, S. (author), Cheng, X. (author), Donkers, M. C.F. (author), Van den Hof, P. M.J. (author)

Identifiability of linear dynamic networks requires the presence of a sufficient number of external excitation signals. The problem of allocating a minimal number of external signals for guaranteeing generic network identifiability in the full measurement case has been recently addressed in the literature. Here we will extend that work by...

journal article 2022

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Single-Leg Forward Hopping via Nonlinear Modes

Calzolari, Davide (author), Della Santina, C. (author), Giordano, Alessandro Massimo (author), Albu-Schaffer, Alin (author)

Implementing dynamic legged locomotion entails stabilizing oscillatory behaviors in complex mechanical systems. Whenever possible, locomotion algorithms should also exploit the improved capabilities of elastic elements added to the structure to improve efficiency and robustness. This work aims to shed some light on implementing generic dynamic...

conference paper 2022

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Online Multi-Robot Task Assignment with Stochastic Blockages

Wilde, N. (author), Alonso-Mora, J. (author)

In this paper we study the multi-robot task assignment problem with tasks that appear online and need to be serviced within a fixed time window in an uncertain environment. For example, when deployed in dynamic, human-centered environments, the team of robots may not have perfect information about the environment. Parts of the environment may...

conference paper 2022

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Secure Control for Cyber-Physical Systems under Malicious Attacks

Wu, Chengwei (author), Yao, Weiran (author), Pan, W. (author), Sun, Guanghui (author), Liu, Jianxing (author), Wu, Ligang (author)

This article investigates the secure control problem for cyber-physical systems when the malicious data are injected into the cyber realm, which directly connects to the actuators. Based on moving target defense (MTD) and reinforcement learning, we propose a novel proactive and reactive defense control scheme. First, the system (A,B) is...

journal article 2021

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Passenger-centric timetable rescheduling: A user equilibrium approach

Binder, S. (author), Maknoon, M.Y. (author), Sharif Azadeh, S. (author), Bierlaire, M. (author)

Unexpected disruptions commonly occur in the railway network, causing delays, and extra cost for operators and inconvenience for passengers by missing their connection and facing overcrowded trains. This paper presents a passenger-centric approach for timetable rescheduling in case of disruption. We study a railway system in which passengers...

journal article 2021

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A dynamic shipment matching problem in hinterland synchromodal transportation

Guo, W. (author), Atasoy, B. (author), Beelaerts van Blokland, W.W.A. (author), Negenborn, R.R. (author)

Hinterland intermodal transportation is the movement of containers between deep-sea ports and inland terminals by using trucks, trains, barges, or any combination of them. Synchromodal transportation, as an extension of intermodal transportation, refers to transport systems with dynamic updating of plans by incorporating real-time information...

journal article 2020

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Container transport inside the port area and to the hinterland

Hu, Q. (author)

This thesis discusses the connection between container terminals and the hinterland railway system. Mathematical models are proposed to formulate the various relevant operations and methods are developed to provide solutions to improve the system performance. This thesis could provide suggestions to decision maker(s) regarding to the improvement...

doctoral thesis 2019

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Target Selection for Tracking in Multifunction Radar Networks: Nash and Correlated Equilibria

Bogdanovic, N. (author), Driessen, J.N. (author), Yarovoy, Alexander (author)

We consider a target selection problem for multitarget tracking in a multifunction radar network from a gametheoretic perspective. The problem is formulated as a noncooperative game. The radars are considered to be players in this game with utilities modeled using a proper tracking accuracy criterion and their strategies are the observed...

journal article 2018