Realistic motion generation for anthropomorphic systems
This work is devoted to Digital Human motion generation, for manufacturing (specifically, for design, maintenance, operator training, workstation design and ergonomics, ...), health (postures for surgery, rehabilitation, ...), or entertainment industry (animation for games, movies,...).
Based on complementary skills and developments of Gepetto LAAS team, and CEA LIST team, in terms of path planning (HPP), dynamic motion control of anthropomorphic systems, the objective of this post doc is to combine both approaches, a global one, dealing mainly with geometric and quasi-static constraints and characteristics, and a local one, dealing with dynamics and taking into account human movement characteristics (motor primitives, minimizing cost criteria, etc ...).
Model evolution management and mastering
Designing ever more complex systems needs for new paradigms in order to face all the new challenges as improving safety while reducing time and cost to market. Paradigms, mainly active models and model transformations, promoted by model-driven engineering are providing efficient solutions to deal with those issues. However, as promoted in the series of international workshops on model and evolution (www.modse.fr), model (co-)evolution and consistency management become crucial activities to cope with the natural changes of any system. In fact, there is an increasing need for more disciplined techniques and engineering tools to support a wide range of model evolution activities, including model-driven system evolution, model differencing, model comparison, model refactoring, model inconsistency management, model versioning and merging, and (co-)evolution of models.
As part of this project, the LISE want especially to consider model evolution management under both next perspectives:
- The first issue is to enable modelers to manage the evolution of their models. They should be able to follow the changes that have been made within a model by providing as for example “track changes” mode in the modeling environment.
- The second issue concerns the problem of model versioning. The users need here to manage and use multiple versions of their models in a collaborative way.
Planning energy consumption within an eco-district
Energy consumption and production are changing, and the birth of eco-districts is now a reality which is a continuation of these changes. Eco-districts consists in grouping within the same territory entities which consume or produce energy and in managing these resources locally.
Alongside these developments, homes, shops and even offices are increasingly equipped with communicating sensors and intelligent devices that can be controlled remotely. It is therefore possible to control these devices taking into account several factors: the financial or environmental cost of energy consumed, the respect of comfort desired by the people and the intent of the directors of the eco-district. Many algorithms have been developed in order to plan and control devices more or less autonomous, while expert systems have often been excluded because of their lack of expressiveness in this area. The goal of this postdoctoral fellowship is to check if fuzzy expert systems can be used to plan devices which consume a source of energy.
Automatic generation of dynamic code generators from legacy code
Context
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Our laboratory is developing a technology for dynamic code generation around a tool called deGoal. deGoal is a tool designed to build specialized code generators (also known as compilettes) customized for each computing kernel we want to accelerate in an application. Such compilettes are designed with the aim to perform data- and architecture-dependent code optimizations and code generation at runtime. Furthermore, compilettes provide very fast code generation and low memory footprint. This approach is fundamentally different from the standard approach for dynamic compilation as used for example in Java Virtual Machines.
In order to target computing architectures that include domain-specific accelerators and to raise the level of abstraction of the source code of compilettes, deGoal uses a dedicated language. This language provides the best performance we can achieve from our technology, and has demonstrated its ability to achieve good performance improvements compared to highly optimised static code. However, the drawback is that one needs to rewrite the source code of a computing kernel from scratch in order to build a new compilette.
Goal
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The goal of this PostDoc is to implement an automatic generator of compilettes able to work from existing source code (typically: ANSI C), and able to be integrated in an industry-grade code generation toolchain.
Distributed multiagent resources allocation. Application to district heating
Heating district networks in France fed more than one million homes and deliver a quantity of heat equal to about 5% of the heat consumed by the residential and tertiary sector. Therefore, they represent a significant potential for the massive introduction of renewable and recovery energy. However, heating networks are complex systems that must manage large numbers of consumers and producers of energy, and that are distributed in extended and highly branched geographical zones. The aim of the SIGMA project, realized in collaboration among the CEA-LIST and the CEA-LITEN, is to implement an optimal and dynamic management of heating networks. We propose a multidisciplinary approach, by integrating the advanced network management using Multi-Agent Systems (MAS), by taking into account spatial constraints using Geographic Information Systems (GIS) and by considering simplified physical models of transport and recovery of heat.
The post-doc’s goal is to design mechanisms for dynamically allocating resources that consider the geographical information from the GIS and the predictions of consumption, production and losses calculated with the physical models. In this way, several characteristics of the network will be considered: the continuous and dynamic aspect of the resource; sources with different behaviors, capabilities and production costs; the dependence of consumption / production to external aspects (weather, energy price); the internal characteristics of the network (losses, storage capacity). The coupling with a GIS should allow implementing self-configuration mechanisms for the management of different networks and different levels of granularity obtained by reduction of the original GIS. The MAS should dynamically establish the link between the suitable simplified models and the desired level of granularity and then it will create the agents needed to represent the system.
Real time low cost algorithms for brain computer interface with multiple degrees of freedom
The topic of the postdoctoral project is the optimization of BCI methods and algorithms for medical application in humans (quadriplegic subjects).
Namely the particular goal of the postdoctoral fellow will be optimization and the acceleration of calculation to allow multiple degrees of freedom (up to 26) in real time. Selecting the appropriate features subset will improve the computational efficiency and the quality of control. To this purpose the algorithms of sparse modeling will be applied.
To map ECoG recordings to the spatial-temporal-frequency space, continuous wavelet transform (CWT) is applied. Optimization will include the implementation of low cost CWT and C++ coding.
The project will include the test and the adaptation of BCI algorithms to wireless signal transmission with the implant WIMAGINE.
Finally the adaptation of algorithms to medical environment of quadriplegic subjects (the use of imaginary tasks, presence of stimuli in the signal, the restricted duration of experiments) will be under responsibility of postdoctoral scientist.
Simultaneous Localisation and Mapping with an RGB-D camera based on a direct and sparse method
Recent advances in the methods of locating a device (smartphone, robot) in relation
to its environment make it possible to consider the deployment of augmented reality solutions and autonomous robots. The interest of RGB-D cameras in such a context is notable since it allows to directly acquire the depth map of the perceived scene.
The objective of this post docorate consists in developping a new SLAM (Simultaneous Localisation and Mapping) method relying on a depth sensor.
To reach a solution both robust, accurate and with small CPU/memory comsumption, the depth image will be exploited though a direct and sparse approach. The resulting solution will be then combined with the solution of "RGB SLAM Constrained to a CAD model" developped in our laboratory, resulting finaly in an "RGB-D SLAM Constrained to a CAD model"
Application of formal methods for interferences management
Within a multidisciplinary technological research team of experts in SW/HW co-design tools by applying formal methods, you will be involved in a national research project aiming at developing an environment to identify, analyze and reduce the interferences generated by the concurrent execution of applications on a heterogeneous commercial-off-the-shelf (COTS) multi-core hardware platform.
Abstract interpretation of ACSL annotations
Frama-C is a set of tools dedicated
to the analysis of C software. In Frama-C, different analyses
techniques are implemented as plug-ins within the same framework.
Part of the glue that holds the various plug-ins together is
the ACSL annotation language. ACSL is a formal specification
language for C programs.
Each verification plug-in is supposed to interpret ACSL
annotations as best it can. A plug-in can also, when it needs to
make an assumption, express it as an ACSL property so that
another plug-in can be used to verify this assumption.
This post-doctoral position consists in improving the precision of Frama-C’s value analysis, based on Abstract Interpretation, for constructs that are not currently handled. The treatment of some constructs will require specific abstract domains to be designed.
http://frama-c.com
http://frama-c.com/value.html
http://frama-c.com/acsl.html