Combining computer sciences and biology, the laboratory develops a broad range of knowledge in the bioinformatics area and especially for the study of biological systems called biological networks. The laboratory focuses on both continuous and discrete modelling of these networks, on the statistical learning for their identification, on the integration and biological data mining, the prediction of non-coding RNAs structures in genome sequences and on the study of cellular micro-environment evolution, based on the experimentation.
Being an expert in automation, mechanics, robotics, and augmented reality, the laboratory designs, develops and evaluates assistive systems for a person in his environment (indoor or outdoor). The problem is to remove technological and scientific obstacles allowing perception, action and decision support for both an individual and a “robot” assistant interacting with an intelligent environment (ambient robotics, driver assistance, mixed reality).
Mixing together the skills in modelling, perception, optimisation and control, the laboratory develops systems which include a flotilla of road or flying vehicles or a mixed set of a dozen of programmable or dedicated processors. “Autonomous” means that agents in this system have a behaviour laid down by their interests and by the system's rules. “Smart” means that the system has been designed in an “optimal” way, that is to say it can fulfil its functions at the lower cost and/or with great efficiency.
This theme focuses on the controlled design of open critical systems, that is to say systems which have to be able to respond properly to any kind of modifications of the environment, even unexpected, and to find an appropriate behaviour. This research revisits the scientific frameworks such as specification, programming and prototyping in the specific case of open systems.