DESCRIPTION :
The infrastructures (road network, bridges, buildings, ...) are among the most important elements of the public heritage. Operators are responsible for maintaining, operating, developing, replacing and preserving this heritage while ensuring careful management of budgetary and human resources. Today, these infrastructures are put to the test by climate change (increase in the frequency of extreme phenomena which in particular favor floods and land movements). Users are also extremely attentive to questions of safety and comfort related to the use of infrastructure but also to environmental issues relating to their construction and maintenance.
The ROAD-AI Challenge objective is to design a multi-robot system comprising ground vehicles and aerial drones collaborating in the collection of data on structures with on-board sensors. Aerial drones seem to be a very promising solution for data acquisition because they can have points of view not obscured by obstacles and access structures more easily. On the other side, the ground vehicle seems better appropriated to supervise the mission of data acquisition for environment exploration and mapping.
Mission confiée
In this Postdoc, we want to study active strategies of data acquisition involving a master robot (the ground vehicle) and two slave robots (aerial robots) in order to optimize in terms of accuracy and stability the mapping of the environment. Each robot will be equipped with its own large field vision with a time stamping. We assume also that synchronized velocity control inputs can be sent to the ground and aerial robots. The master robot centralizes the information and manages the multi-robots formation. One robot of the formation, so-called the leader (not necessary the master) is manually driven by a human operator who ensures the completness of the exploration of the scene.
The first scientific problem we want to deal with in this Postdoc will be to guarantee a stable structure of the robot formation in the reference frame of the master robot. The choice of an optimal structure of the formation will be directed by the task objectives (i.e., exploration context, optimization of the map acquisition…). Recent works on Cooperative Multi-Robots Systems [1],[2],[3],[4],[5],[6] will be used to organize and to manage the formation taking into account the navigability constraints. Considering that each robot can be observed by at least one of the other, we intend to realize and to control the formation by means of sensor-based control and visual servoing techniques [7], [8].
The second scientific concern will be to investigate how we can use the constraints induced by the formation to stabilize the ill-posed problem of SLAM (Simultaneous Localization and Mapping). SLAM is a key problem in mobile robotic which consists of exploiting the observation of the environment for conjointly estimating the robot's trajectory and building a map of the environment [9],[10], [11]. Basically, the robot's trajectory is built thanks to an odometry method integrating an estimate of the displacement. As result, we observe a drift in the trajectory leading to a distorted map. A classical solution to minimize this drift and to correct the distortion is the use of closed loop methods based on the re-observation of landmarks and a backpropagation of the drift along the trajectory [12],[13]. To be efficient a sufficient large number of landmarks dispatched all along the trajectory have to be re-observed. Considering the constraints
introduced by the structure of formation described above, it seems possible to formulate a SLAM problem for collaborative robots as a global optimization problem involving the trajectories of the different robots AND the constraints due to the structure of the formation. In such a case, we expect to largely simplify or, maybe to eliminate, the problem of drift and the need of closed loop methods.
The system will be evaluated on Inria robots on a structure known to the Cerema services, for which the civil engineering service will be requested. For the experimental evaluation, the candidate will work in close collaboration with a PhD student and an R&D engineer who will be in charge of the implementation of the multi-robot system.
Reference:
[1] D. Koung, O. Kermorgant,I. Fantoni, L. Belouer. « Cooperative Multi-Robot Object Transportation System Based on Hierarchical Quadratic Programming", June 2021.IEEE Robotics and Automation Letters PP(99):1-1.
[2] G. Arechavaleta, A. Morales-Díaz, H. M. Pérez-Villeda, and M. Castelán "Hierarchical Task-Based Control of Multirobot Systems With Terminal Attractors", Control Systems Technology, IEEE Transactions on 25(1):1-8, April 2016.
[3] Two-layers Workspace: A New Approach to Cooperative Object Transportation with Obstacle Avoidance for Multi-Robot System. January 2022, IEEE Access PP(99):1-1.
[4] L. Zhang, Y. Sun, A. Barth and O. Ma. "Decentralized Control of Multi-Robot System in Cooperative Object Transportation Using Deep Reinforcement Learning", January 2020.
[5] G. Lozenguez, L. Adouane, A. Beynier, Abdel-Illah Mouaddib, P. Martinet. Punctual versus continuous auction coordination for multi-robot and multi-task topological navigation, Autonomous Robot (2016) 40:599-613.
[6] D. Koung, I. Fantoni, O. Kermorgant and L. Belouaer. Consensus-based formation control and obstacle avoidance for nonholonomic multi-robot system, International Conference on Control, Automation, Robotics and Vision (ICARCV) December 13-15, 2020. Shenzhen, China.
[7] S. A. Hutchinson, G. D. Hager, and P. I. Corke. A tutorial on visual servo control. IEEE Trans. Robot. Automat., 12(5):651--670, Oct. 1996.
[8] E. Malis and P. Rives. "Robustness of image-based visual servoing with respect to depth distribution errors". In IEEE International Conference on Robotics and Automation, September 2003.
[9] R. Mur-Artal and J. D. Tardós, "ORB-SLAM2: An Open-Source SLAM System for Monocular, Stereo, and RGB-D Cameras," in IEEE Transactions on Robotics, vol. 33, no. 5, pp. 1255-1262, Oct. 2017.
[10] Georg Klein and David Murray, "Parallel Tracking and Mapping for Small AR Workspaces"
In Proc. International Symposium on Mixed and Augmented Reality (ISMAR'07, Nara).
[11] M. Meilland, A. Comport, and P. Rives. "Dense omnidirectional rgb-d mapping of large-scale outdoor environments for real-time localization and autonomous navigation". Journal of Field Robotics, 32(4):474-503, 2015.
[12] Kin Leong Ho, P. Newman. "Loop closure detection in SLAM by combining visual and spatial appearance", Robotics and Autonomous Systems 54 (2006).
[13] A. Chapoulie, P. Rives, D. Filliat. "A spherical representation for efficient visual loop closing." International Conference on Computer Vision Workshops (ICCV Workshops) , 2011.
Principales activités
The work will be broken down into stages as follows:
* Bibliography on Visual Servoing, mission planning for collaborative robots, SLAM techniques, nonlinear optimization
* Implementation of the most efficient state-of-the-art techniques
* Study and implementation of a robot's formation specification and control using visual servoing
* Study and implementation of a collaborative SLAM scheme
* Comparison with state-of-the-art localization techniques
* Validation with remotely operated robots (not autonomous)
* Writing articles for international conferences and journals, writing project reports
Code d'emploi : Chargé de Recherches (h/f)
Domaine professionnel actuel : Scientifiques
Niveau de formation : Bac+8
Temps partiel / Temps plein : Plein temps
Type de contrat : Contrat à durée indéterminée (CDI)
Compétences : Intelligence Artificielle, Vision par Ordinateur, Réalité Augmentée, Programmation Informatique, Linux, Python (Langage de Programmation), OpenCV, Technologie Open Source, Conception et Développement de Logiciel, Apprentissage par Renforcement, Système d'Exploitation Robot, Git, KS123K75YYK8VGH90NCS, Polyvalence, Ponctualité, Enthousiasme, Esprit d'Équipe, Vente aux Enchères, Systèmes Automatisés, Système Autonome, Travaux de Construction, Génie Civil, Systèmes de Contrôle, Collecte de Données, Protection de l'Environnement, Ressources Humaines, Gestion des Infrastructures, Revue (Publication Périodique), Maintenance et Dépannage, Approche Pluridisciplinaire, Recherche Post-Doctorale, Recherche et Développement, Conception et Réalisation en Robotique, Servomécanisme, Système de Son Stéréophonique, Réseaux de Transport, Capteurs, Changement Climatique
Courriel :
Ezio.Malis@inria.fr
Téléphone :
0139635511
Type d'annonceur : Employeur direct