Papers by assia belbachir
Preliminary results on UAV-based forest fire localization based on decisional navigation
Efficient localization of forest-fires based Unmanned Aerial Vehicles (UAVs) represents valuable ... more Efficient localization of forest-fires based Unmanned Aerial Vehicles (UAVs) represents valuable assessment. Due to the fast deployment of UAVs, it is practical to use them. For forest fire detection purposes, usually the area to explore is unknown, thus existing strategies use an automatic coverage exploration strategy. However, such approach is not efficient in terms of exploration time since the mission execution and achievement in an unknown environment that needs a strong vehicle decision and control. Based on this observation, we improved the localization mission by a decision-based strategy resulting from a probabilistic model based on the temperature in order to estimate the distance towards the forest-fire. The UAV optimizes its trajectory according to the state of the forest-fire knowledge by using a map to represent its knowledge and updates it at each step of its exploration. We show in this paper that our planning and control methodology for forest-fire localization is efficient. Simulation results are carried out to evaluate the proposed methodology and approves our claim.
HAL (Le Centre pour la Communication Scientifique Directe), Oct 10, 2018
L'environnement dynamique des systèmes ambiants offre des informations contextuelles aux agents i... more L'environnement dynamique des systèmes ambiants offre des informations contextuelles aux agents intelligents qui s'y déploient. Dans de tels environnements, ces agents peuvent-ils collaborer pour mieux atteindre leurs objectifs individuels et collectifs, et ce en considérant leurs intentions multiples ? Cette coopération dépendra fortement des intentions des agents. Dans cet article, nous proposons de doter les agents ambiants d'un mécanisme de planification contextuelle appelé CPS qui peut s'étendre dans un contexte collectif. Nous présentons d'abord le CPS qui génère des plans contextuels optimaux pour un seul agent tout en satisfaisant plusieurs de ses intentions et en préservant la consistance du plan. Ensuite, nous étendons ce mécanisme coopératif de planification pour prendre en considération plusieurs agents ambiants. Appelé CCPS (collective CPS), il permet aux agents de déléguer partiellement leur plan et de collaborer durant l'exécution de leurs plans. Un scenario de travail extrait du Campus Intelligent est implémenté et discuté.
A Force Field Reinforcement Learning Approach for the Observation Problem
Springer eBooks, 2022
Multiagent and Grid Systems
This paper addresses the problem of ecological ocean pollution by using semi-autonomous unmanned ... more This paper addresses the problem of ecological ocean pollution by using semi-autonomous unmanned vehicles. A hybrid approach for unmanned vehicles cooperation (HA-UVC) is presented for unmanned aerial vehicles (UAV) to monitor ocean regions and clean up their dirty areas with a swarm of unmanned surface vehicles (USV). Thus, the proposed HA-UVC addresses the problem of trajectory planning, where unmanned vehicles must find a trajectory from the starting position to the goal position while avoiding static obstacles. Consequently, two solutions are proposed in order to manage the trajectory planning problem for the semi-autonomous USV Swarm. The first solution is performed by a modified genetic algorithm (GA). However, the second one is achieved by a proposed Cartesian coordinate algorithm (CCA). In order to optimize the applicable performance, the proposed solutions make it possible to detect and reduce the level of pollution in ocean regions, while avoiding obstacles and failures of unmanned vehicles.
A decision-making architecture for observation and patrolling problems using machine learning
2021 10th International Congress on Advanced Applied Informatics (IIAI-AAI)
Journal of Intelligent & Robotic Systems
Incidents of hydraulic or oil spills in the oceans/seas or ports occur with some regularity durin... more Incidents of hydraulic or oil spills in the oceans/seas or ports occur with some regularity during the exploitation, production and transportation of petroleum products. Immediate, safe, effective and environmentally friendly measures must be adopted to reduce the impact of the oil spill on marine life. Due to the difficulty to detect and clean these areas, semi-autonomous vehicles can make a significant contribution by implementing a cooperative and coordinated response. The paper proposes a concept study of Hybrid Monitoring Detection and Cleaning System (HMDCS-UV) for a maritime region using semiautonomous unmanned vehicles. This system is based on a cooperative decision architecture for an unmanned aerial vehicle to monitor and detect dirty zones (i.e., hydraulic spills), and clean them up using a swarm of unmanned surface vehicles. The proposed solutions were implemented in a real cloud and were evaluated using different simulation scenarios. Experimental results show that the proposed HMDCS-UV can detect and reduce the level of hydraulic pollution in maritime regions with a significant gain in terms of energy consumption.
This paper deals with the problem of monitoring and<br> cleaning dirty zones of oceans usin... more This paper deals with the problem of monitoring and<br> cleaning dirty zones of oceans using unmanned vehicles. We present<br> a centralized cooperative architecture for unmanned aerial vehicles<br> (UAVs) to monitor ocean regions and clean dirty zones with the help<br> of unmanned surface vehicles (USVs). Due to the rapid deployment<br> of these unmanned vehicles, it is convenient to use them in oceanic<br> regions where the water pollution zones are generally unknown. In<br> order to optimize this process, our solution aims to detect and reduce<br> the pollution level of the ocean zones while taking into account the<br> problem of fault tolerance related to these vehicles.
Computational Intelligence and Adaptation in VANETs: Current Research and New Perspectives
2018 International Joint Conference on Neural Networks (IJCNN), 2018
The increasing number of moving vehicles along roads and the lack of supporting infrastructure is... more The increasing number of moving vehicles along roads and the lack of supporting infrastructure is a wellestablished problem. Major consequences are augmenting of traffic jams, accidents, fuel consumption and pollution. Vehicular Ad hoc NETworks (VANETs) represent opportunities to deal with the aforementioned problems. In VANETS, efficiency and safety to applications are provided using communication support. In efficiency applications, each vehicle is aware of its location. Using this information and communication support, vehicles collaborate to reduce travel time and to improve mobility. In contrast, safety applications aim to reduce or even avoid accidents, and must obey strong timing constraints. In this context, VANETs applications can benefit from Computational Intelligence (CI) and adaptive approaches to implement the required demands. Thus, the contribution of this paper is twofold: $( i)$ we discuss how VANETs can benefit from CI and Artificial Intelligence techniques to make transportation networks more efficient regarding to safety applications, and, $( ii)$ we report our current work and new directions in the development of efficiency applications to VANETs using adaptation and CI techniques.
2013 IEEE Intelligent Vehicles Symposium (IV), 2013
For decades, scientists have dreamed of building autonomous cars that can drive without a human d... more For decades, scientists have dreamed of building autonomous cars that can drive without a human driver. Progress in this kind of research recently received an increasing attention in car industries. There are many autonomous car models recently developed. However, they are still infancy since they still lack efficiency and reliability. To obtain efficient and reliable systems, the validation process plays an important role. Nowadays, the validation is strongly related to the number of kilometers of drive. Thus, simulation techniques are used before going into real world driving. We focused our work on developing a methodology to smothly move from simulation into real world car driving. We defined a versatile architecture that simplifies the evaluation of different types of algorithms. Several evaluation systems are shown and discussed.
Procedia Computer Science, 2019
In this paper, we propose a self-adaptive mechanism for traffic regulation based on cooperative a... more In this paper, we propose a self-adaptive mechanism for traffic regulation based on cooperative agents. We focus our study on the intersection behaviour, using intelligent agents to represent the infrastructure elements, which cooperate among each other in order to minimize traffic congestion. While the agents are capable of cooperating among themselves, the cooperative behaviour is not pre-defined, as it emerges from the agent interactions at a local level. We also explain our results from simulation experiments involving the proposed mechanism, comparing it with other traffic congestion regulation systems currently in use.
A Cooperative Architecture to Localize Targets for Underwater Vehicles
This paper reports the architecture of a simulator which is able to evaluate sensors, path planne... more This paper reports the architecture of a simulator which is able to evaluate sensors, path planners and controllers of the advanced driving-assistance systems (ADAS). The outstanding feature of this simulator is that it is able to evaluate algorithms by giving scores. The implementation of the algorithms requires several tools such as Pro-SiVICTM. To have a good evaluation of the developed algorithms, we give a list in this paper of the requirements for an ADAS simulator. The simulator architecture and the developed algorithms are tested in several ADAS scenarios. Using Pro-SiVICTM as a simulator, we are now able to evaluate different algorithms for ADAS. Keywords-Simulation architecture; Pro-SiVICTM; Evaluation; ADAS.
Self-vehicle Positioning Using Smart Infrastructures
Localization is crucial to many vehicular applications and is usually carried out using the Geogr... more Localization is crucial to many vehicular applications and is usually carried out using the Geographical Positioning System (GPS). However, when the GPS signal is unavailable, other solutions can be applied such as camera images and Inertial Navigation System (INS) to know about its movement in order to calculate the actual positions. However, such techniques can be costly in consumption in terms of processing time and energy. Moreover, INS is subject to cumulative errors. In order to improve positioning, information coming from other sensors can be a solution. Thus, this paper proposes a self-adaptive protocol for vehicle localization using smart infrastructure support in GPS free environments. In this context, an autonomous vehicle with unknown localization interacts with the infrastructure sensors to infers its position. Experiments with the adaptive protocol were conducted in a robotic platform. Our obtained results are promising and the maximum error percentage that our localiz...
Fostering Agent Cooperation in AmI: A Context-Aware Mechanism for Dealing with Multiple Intentions
Ambient Intelligent (AmI) environments dynamically provide contextual information to intelligent ... more Ambient Intelligent (AmI) environments dynamically provide contextual information to intelligent agents that interact with them. In such environments, could these agents cooperate to improve their goal achievement, considering multiple intentions from several agents? With multiple agents, cooperation will depend on each agent’s own intentions. Agents adapt to dynamic changes in the environment using context-aware planning mechanisms such as the Contextual Planning System (CPS), which proposes an optimal plan for a single agent based on the current context. In this paper we present the Collective CPS (CCPS), an opportunistic cooperative planning mechanism for multiple agents in AmI environments. CCPS allows agents to partially delegate their own plans or to collaborate with other agents’ plans during their execution, while retaining individual planning capabilities. A working scenario is shown for a realistic AmI environment, such as a Smart Campus.
A Hybrid Architecture for Cooperative UAV and USV Swarm Vehicles
This paper is interested in the problem of monitoring and cleaning dirty zones of oceans, dealing... more This paper is interested in the problem of monitoring and cleaning dirty zones of oceans, dealing with the notion of path planning for semi-autonomous unmanned vehicles. We present a hybrid cooperative architecture for unmanned aerial vehicle (UAV) to monitor ocean region and clean dirty zones with the help of swarm unmanned surface vehicles (USVs). In the path planning problem, unmanned vehicles must plan their path from the starting to the goal position. In this article, we propose a solution to handle the problem of trajectory planning for semi-autonomous cleaning vehicles. This solution is based on the proposed Genetic Algorithm (GA). In order to optimize this process, our proposed solution detects and reduces the pollution level of the ocean zones while taking into account the problem of fault tolerance related to these vehicles.
Nous nous interessons a l'architecture de robots marins et sous-marins autonomes dans le cadr... more Nous nous interessons a l'architecture de robots marins et sous-marins autonomes dans le cadre de missions necessitant leur cooperation. Cette cooperation s'avere difficile du fait que la communication (acoustique) est tres contrainte en termes de debit et de portee. Notre travail se place dans le contexte de missions d'exploration pour detecter des elements particuliers sur les fonds marins, et en particulier des sources d'eau chaude. Pour cela, le vehicule sous-marin parcours des segments de droite pre-planifies et rejoint des points de rendez-vous (points de communication). Ces derniers permettent d'assurer le suivi de bon deroulement de la mission, mais surtout de mettre en oeuvre des schemas de cooperation entre les vehicules sous-marins. Au fur et a mesure de l'exploration, les sous-marins construisent et mettent a jour une representation de l'environnement qui decrit les probabilites de localisation de sources. Une approche adaptative exploite ces...
Gestion d'intentions multiples pour agents ambiants coopératifs (présentation courte)
Nous nous interessons a l’architecture de robots marins et sous-marins autonomes dans le cadre de... more Nous nous interessons a l’architecture de robots marins et sous-marins autonomes dans le cadre de missions necessitant leur cooperation. Cette cooperation s’avere difficile du fait que la communication (acoustique) est de faible qualite et de faible portee. Afin d’illustrer notre travail, nous nous interessons a un scenario de localisation d’une source d’eau chaude sous-marine. Pour cela, le vehicule sous marin parcourt des segments de droite et rejoint des points de rendez-vous (points de communication). Ces derniers sont importants car ils permettent la mise en œuvre d’une cooperation entre les vehicules sous-marins. Au fur et a mesure du deplacement d’un vehicule, celui ci detecte (grâce a ses capteurs) la possibilite de traverser une zone pouvant contenir une source d’eau chaude. Afin de localiser une source, on doit permettre au vehicule de modifier sa trajectoire initiale, tout en s’assurant d’atteindre le point de rendez-vous. Nous presentons nos travaux effectues dans cette ...
In this paper, we propose a self-adaptive approach to build a smart traffic light management deal... more In this paper, we propose a self-adaptive approach to build a smart traffic light management dealing with intersections. This approach relies on the multiagent systems architecture, suitable to support a distributed and collaborative mechanism of regulation while taking into account dynamic changes in the traffic flow. In our solution, the agents model the intersections and can decide how long is the duration of traffic lights according to their perception of the traffic flow. Each intersection agent uses a behavior tree to update the traffic light status (i.e. switch from green to red lights and vice-versa), changing the duration of each status dynamically, according to the number of cars perceived in each intersection. We also demonstrate how dynamic traffic control policies can be used in a collaborative scenario to regulate traffic flow.
Lightweight Cooperative Self-Localization as Support to Traffic Regulation for Autonomous Car Driving
Self-localization is a basic service for Intelligent Transportation Systems (ITS) such as traffic... more Self-localization is a basic service for Intelligent Transportation Systems (ITS) such as traffic regulation services. Most of the used techniques are based on integration of Inertial Navigation System (INS) and Global Positioning System (GPS). However, navigation through areas such as tunnels, where GPS coverage is vulnerable, obliges the use of a different approach. Based on this observation, we designed and implemented a lightweight cooperative positioning algorithm based on Adaptive Localization Protocol (ALP). In this paper, we apply our method as support to an intersection service for traffic regulation, in which a group of concurrent cars shares an intersection/critical section. We found that our algorithm improves car position and regulates the traffic.
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Papers by assia belbachir