Safety of autonomous vehicles: A survey on Model-based vs. AI-based approaches

The growing advancements in Autonomous Vehicles (AVs) have emphasized the critical need to prioritize the absolute safety of AV maneuvers, especially in dynamic and unpredictable environments or situations. This objective becomes even more challenging due to the uniqueness of every traffic situation/condition. To cope with all these very constrained and complex configurations, AVs must have appropriate control architectures with reliable and real-time Risk Assessment and Management Strategies (RAMS). These targeted RAMS must lead to reduce drastically the navigation risks. However, the lack of safety guarantees proves, which is one of the key challenges to be addressed, limit drastically the ambition to introduce more broadly AVs on our roads and restrict the use of AVs to very limited use cases. Therefore, the focus and the ambition of this paper is to survey research on autonomous vehicles while focusing on the important topic of safety guarantee of AVs. For this purpose, it is proposed to review research on relevant methods and concepts defining an overall control architecture for AVs, with an emphasis on the safety assessment and decision-making systems composing these architectures. Moreover, it is intended through this reviewing process to highlight researches that use either model-based methods or AI-based approaches. This is performed while emphasizing the strengths and weaknesses of each methodology and investigating the research that proposes a comprehensive multi-modal design that combines model-based and AI approaches. This paper ends with discussions on the methods used to guarantee the safety of AVs namely: safety verification techniques and the standardization/generalization of safety frameworks

Control Architecture for Cooperative Mobile Robots using Multi-Agent based Coordination Approach

National audienceThis paper is about a Multi-Agent based solution to control and coordinate team-working mobile robots moving in unstructured environments. Two main contributions are considered in our approach. The rst contribution of this paper is about the Multi-Agents System to Control and Coordinate teAmworking Robots (MAS2CAR) architecture, a new architecture to control a group of coordinated autonomous robots in unstructured environments. MAS2CAR covers three main layers: (i) the Physical Layer (ii) the Control Layer and (iii) the Coordination Layer. The second contribution of this paper is about the multi-agent system (MAS) organisational models aiming to solve the key cooperation issues in the coordination layer, the software components designed based on Utopia a MAS framework which automatically build software agents, thanks to a multi-agent based organisational model called MoiseInst . We provide simulation results that exhibit robotics cooperative behavior related to our scenario, such as multi-robots navigation in presence of obstacles (including trajectory planning, and reactive aspects) via a hybrid control

Punctual versus continuous auction coordination for multi-robot and multi-task topological navigation

International audienceThis paper addresses the interest of using Punctual versus Continuous coordination for mobile multi-robot systems where robots use auction sales to allocate tasks between them and to compute their policies in a distributed way. In Continuous coordination, one task at a time is assigned and performed per robot. In Punctual coordination, all the tasks are distributed in Rendezvous phases during the mission execution. However , tasks allocation problem grows exponentially with the number of tasks. The proposed approach consists in two aspects: (1) a control architecture based on topo-logical representation of the environment which reduces the planning complexity and (2) a protocol based on Sequential Simultaneous Auctions (SSA) to coordinate Robots' policies. The policies are individually computed using Markov Decision Processes oriented by several goal-task positions to reach. Experimental results on both real robots and simulation describe an evaluation of the proposed robot architecture coupled wih the SSA protocol. The efficiency of missions' execution is empirically evaluated regarding continuous planning

Simultaneous Auctions for "Rendez-Vous" Coordination Phases in Multi-robot Multi-task Mission

International audienceThis paper presents a protocol that permits to automatically allocate tasks, in a distributed way, among a fleet of agents when communication is not permanently available. In cooperation settings when communication is available only during short periods, it is difficult to build joint policies of agents to collectively accomplish a mission defined by a set of tasks. The proposed approach aims to punctually coordinate the agents during "Rendezvous'' phases defined by the short periods when communication is available. This approach consists of a series of simultaneous auctions to coordinate individual policies computed in a distributed way from Markov decision processes oriented by several goals. These policies allow the agents to evaluate their own relevance in each task achievement and to communicate bids when possible. This approach is illustrated on multi-mobile-robot missions similar to distributed traveling salesmen problem. Experimental results (through simulation and on real robots) demonstrate that high-quality allocations are quickly computed

Calcul distribué de politiques d'exploration pour une flotte de robots mobiles

National audienceCe papier présente une architecture multirobots permettant une allocation automatique de plusieurs objectifs sur une flotte de robots. Le challenge consiste à rendre des robots autonomes pour réaliser coopérativement leur mission sans qu'un plan soit prédéfini. Cette architecture, appelée PRDC, est basée sur 4 modules (Perception, Représentation, Délibération et Contrôle). Nous nous intéressons plus particulièrement au module de délibération en considérant le problème des voyageurs de commerce coopératifs dans un environnement incertain. L'objectif des robots est alors de visiter un ensemble de points d'intérêt représentés dans une carte topologique stochastique (Road-Map). Le processus proposé pour la construction des politiques collaboratives est distribué. Chaque robot calcule ses politiques individuelles possibles de façon à négocier collectivement l'allocation des points d'intérêt entre les membres de la flotte. Enfin, l'approche est évaluée via un important nombre de simulation

Map Partitioning to Approximate an Exploration Strategy in Mobile Robotics

International audienceIn this paper, an approach is presented to automatically allocate a set of exploration tasks between a fleet of mobile robots. The approach combines a Road-Map technique and Markovian Decision Processes (MDPs). The addressed problem consists of exploring an area where a set of points of interest characterizes the main positions to be visited by the robots. This problem induces a long term horizon motion planning with a combinatorial explosion. The Road-Map allows the robots to represent their spatial knowledge as a graph of way-points connected by paths. It can be modified during the exploration mission requiring the robots to use on-line computations. By decomposing the Road-Map into regions, an MDP allows the current group leader to evaluate the interest of each robot in every single region. Using those values, the leader can assign the exploration tasks to the robots

Toward Smooth and Stable Reactive Mobile Robot Navigation using On-line Control Set-points

International audience— This paper deals with the challenging issue of on-line mobile robot navigation in cluttered environment. Indeed, it is considered in this work, a mobile robot discovering the environment during its navigation, it should thus, to react to unexpected events (e.g., obstacles to avoid) while guaranteeing to reach its objective. Nevertheless, in addition to avoid safely and on-line these obstacles, it is proposed to enhance the smoothness of the obtained robot trajectories. Otherwise, to quantify this smoothness, suitable indicators were used. Specifically, this paper proposes to appropriately link on-line set-points defined using elliptic limit-cycle trajectories with a multi-controller architecture which guarantees the stability (according to Lyapunov synthesis) and the smoothness of the switch between controllers. Moreover, a comparison between fully reactive mode (the aim of this paper) and planned mode is given through the proposed control architecture which could exhibits the two aspects. Many simulations in cluttered environments permit to confirm the reliability and the robustness of the overall proposed reactive control

Distributed and Reactive Multi-robot Navigation in Cluttered Environment

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Orbital Obstacle Avoidance Algorithm for Reliable and On-Line Mobile Robot Navigation

International audience— This paper proposes an orbital obstacle avoidance algorithm which permits to obtain safe and smooth robot navigation in very cluttered environments. This algorithm uses specific reference frame which gives accurate indication on robot situation. The robot knows thus if it must avoid the obstacle in clockwise or counterclockwise direction. Moreover, it knows the moment to go into the orbit of the obstacle and the moment to go out. These orbital behaviors are performed using adaptive limit-cycle trajectories. The later with a specific conflicting situations module permit to prevent robot oscillations , local minima and dead ends. The proposed algorithm is embedded in a specific bottom-up control architecture with stability proof given according to Lyapunov synthesis. The overall proposed structure of control allows to decrease significantly the time to reach the target. In fact, according to the proposed algorithm, robot anticipates the collisions with obstacles according to smooth local trajectory modifications. A large number of simulations in different environments are performed to demonstrate the efficiency and the reliability of the proposed control architecture

Architectures de contrôle comportementales et réactives pour la coopération d'un groupe de robots mobiles

The control of a highly dynamic multi-robots system where evolves a large number of reactive autonomous entities constitutes a promising scientific and technological challenge. Indeed, this requires to use robotics entities as elementary as possible, but also requires in term of control, to move more away from centralized and cognitive designs. The approach consists in focusing the control design more on the elementary individual constituting the multi-robots system while taking into account its different local interactions with other robotics entities, which are supposed to cooperate between them. Mastered mass effects can be gotten thus and will permit to enhance at the same time the speed, flexibility and the robustness of the executed complex tasks. The works of research presented in this thesis leave from the principle of a Bottom-Up architectures of control in order to break the inherent complexity of the multi-robots systems. More specifically, we propose a Hierarchical Action Selection Process named HASP which permits at the scale of the robot to coordinate the activity of a set of elementary primitives (behaviors) in a hierarchical and flexible manner, and at the scale of the group of robots, allows a coordination promoting global goals. The performances of the HASP were improved after via the addition of an appropriate mechanism of fusion of actions leading thus to the HHASP (Hybrid-HASP). The formalisms of the genetic algorithms have been used afterwards to propose a methodology, which allow to obtain preponderant parameters for the working of the HHASP. The validation of the results was made through experimentations with mini-robots ALICE and more intensively on statistical studies achieved on a big number of data gotten thanks to MiRoCo (Mini-Robotique Collective) simulator. This simulator have been designed and developed in the framework of our thesis works in order to simulate accurately and rigorously multi-robots systems, which have a strong dynamic of interaction.Contrôler un système multi-robots hautement dynamique au sein duquel évolue un grand nombre d'entités autonomes réactives est un challenge à la fois scientifique et technologique en plein essor. En effet, ceci exige non seulement d'utiliser des entités robotiques les plus élémentaires possibles mais nécessite également au niveau du contrôle, de s'éloigner davantage des conceptions centralisées et cognitives. La démarche consiste à focaliser la conception du contrôle sur l'individu élémentaire constituant le système multi-robots en prenant en compte les différentes interactions locales de cet individu avec les autres entités robotiques avec lesquels il est censé coopérer. Des effets de masse maîtrisés peuvent être ainsi obtenus et vont permettre d'augmenter à la fois la vitesse, la flexibilité et la robustesse d'exécution des tâches complexes entreprises. Les travaux de recherche présentés dans ce mémoire partent du principe d'une conception ascendante (Bottom-Up) des architectures de contrôle et ce afin de briser la complexité inhérente aux systèmes multi-robots. Plus spécifiquement, nous proposons un Processus de Sélection d'Action Hiérarchique appelé PSAH qui permet à l'échelle du robot de coordonner l'activité d'un ensemble de primitives élémentaires (comportements) d'une manière hiérarchique et flexible, et à l'échelle du groupe de robots d'atteindre une coordination entre robots favorisant des buts globaux. Les performances du PSAH ont été améliorées par la suite via l'adjonction d'un mécanisme de fusion d'actions approprié conduisant à un nouveau processus de sélection appelé PSAHH (PSAH-Hybride). Les formalismes des algorithmes génétiques ont été utilisés par la suite pour proposer une méthodologie permettant l'obtention des paramètres prépondérants pour le fonctionnement du PSAHH. La validation des résultats s'est effectuée au travers d'expérimentations sur des mini-robots ALICE et plus largement sur un ensemble d'études statistiques réalisées sur un grand nombre de données obtenu grâce au simulateur MiRoCo (Mini-Robotique Collective). Ce simulateur a été conçu et développé dans le cadre de nos travaux de thèse dans le but de simuler d'une manière précise et rigoureuse des systèmes multi-robots à forte dynamique d'interaction