Section: New Results
Understanding and mastering complex systems
Adaptive control of a complex system based on its multi-agent model
Participants : Vincent Chevrier, Tomas Navarrete.
Laurent Ciarletta (Madynes team, LORIA) is an external collaborator.
Complex systems are present everywhere in our environment: internet, electricity distribution networks, transport networks. These systems have the following characteristics: a large number of autonomous entities, dynamic structures, different time and space scales and emergent phenomena. This work is centered on the problem of control of such systems. The problem is defined as the need to determine, based on a partial perception of the system state, which actions to execute in order to avoid or favor certain global states of the system. This problem comprises several difficult questions: how to evaluate the impact at the global level of actions applied at a global level, how to model the dynamics of an heterogeneous system (different behaviors issue of different levels of interactions), how to evaluate the quality of the estimations issue of the modeling of the system dynamics.
We propose a control architecture[1] based on an “equation-free” approach. We use a multi-agent model to evaluate the global impact of local control actions before applying the most pertinent set of actions.
Associated to our architecture, an experimental platform has been developed to confront the basic ideas or the architecture within the context of simulated “free-riding” phenomenon in peer to peer file exchange networks. We have demonstrated that our approach allows to drive the system to a state where most peers share files, despite given initial conditions that are supposed to drive the system to a state where no peer shares. We have also executed experiments with different configurations of the architecture to identify the different means to improve the performance of the architecture.
Multi Modeling and multi-simulation
Participants : Vincent Chevrier, Christine Bourjot, Benjamin Camus.
Laurent Ciarletta (Madynes team, LORIA) is an external collaborator.
Complex systems generally require to use different points of view (abstraction levels) at the same time on the system in order to capture and to understand all the dynamics and the complexity. Being made of different interacting parts, a model of a complex system also requires simultaneously modeling and simulation (M&S) tools from different scientific fields.
We proposed the AA4MM meta-model [56] is to build a society of models, simulators and simulation softwares that solves the core challenges of multimodelling and simulation coupling in an homogeneous perspective.
This year we focused on systems that naturally involve entities at different levels of description: micro and macro levels with their dynamics and and their articulations : emergence (upward causation, from micro to macro levels) and immergence (downward causation, from macro to micro levels). We relied on Bourgine’s generic view of the relationship between complex phenomenon’s levels and their temporal evolution [50] . We proposed an extension of the AA4MM concepts[13] in order to adapt them to emergence and immergence specifications. A simple example of multi-level modeling of a flocking phenomenon has been implemented to illustrate our proposal.
Robustness of Cellular Automata and Reactive Multi-Agent Systems
Participants : Olivier Bouré, Vincent Chevrier, Nazim Fatès.
Our research on emergent collective behaviours focuses on robustness analysis, that is the behavioural resistance to perturbations in collective systems. We progressed in the knowledge of how to tackle this issue in the case of cellular automata (CA) and multi-agent systems (MAS).
The density classification problem was taken as a simple example for studying how decentralised computations can be carried out with simple cells. Although it is known that this problem can not be solved perfectly, we derived analytic calculations to understand how stochastic cellular automata provide good solutions [3] . A collaboration with mathematicians lead us to study how to extend this result to the infinite-space case [25] and to the 2D finite case [19] .
Two papers resulting from the Amybia projects were published : experimental results on phase transitions obtained with FPGAs [7] and the description on a robotics experiment that demonstrates the robustness of a bio-inspired aggregation method [5] .
The results on asynchronous information transmission in cellular automata were consolidated [2] . Original definitions of asynchronism were also developed in lattice-gas cellular automata [11] , which allows us to complete our spectrum of models for which robustness can be studied analytically and with numerical simulations.
Robotics Systems and Ambiant Intelligence
Robotics systems : autonomy, cooperation, robustness
Local control based platooning
Participants : Alexis Scheuer, Olivier Simonin, François Charpillet, Jano Yazbeck.
We consider decentralised control methods to operate autonomous vehicles at close spacings to form a platoon. We study models inspired by the flocking approach, where each vehicle computes its control from its local perceptions. We investigate different decentralised models in order to provide robust and scalable solutions. Open questions concern collision avoidance, stability and multi-platoon navigation.
In order to reduce the tracking error (i.e. the distance between each follower's path and the path of its predecessor), we developed both an innovative approach [58] and a new lateral control law. This lateral control law reduces the tracking error faster than other existing control laws. This control law, and the experimental results obtained with it, has been submitted to 2013 IEEE International Conference on Robotics and Automation. Its integration with a previously defined secure longitudinal control law [55] has also been studied, and will be submitted soon to 2013 IFAC Intelligent Autonomous Vehicles Symposium.
Adaptation of autonomous vehicle traffic to perturbations
Participants : Mohamed Tlig, Olivier Simonin, Olivier Buffet.
In the context of the European project InTraDE, the problem studied in the context of Mohamed Tlig's PhD thesis is to handle the displacements of numerous IAVs (Intelligent Autonomous Vehicles) in a seaport. Here we assume a supervisor planning the routes of the vehicles in the port. However, in such a large and complex system, different unexpected events can arise and degrade the traffic : failure of a vehicle, human mistake while driving, obstacle on roads, local re-planning, and so on.
We started focusing on a first important sub-problem of space resource sharing among multiple agents: how to ensure the crossing of two opposed flows of vehicles on a road when one of the two paths is blocked by an obstacle. To overcome this problem, blocked vehicles have to coordinate with vehicles of the other side to share the road and manage delays. The objective is to improve traffic flow and reduce the emergence of traffic jam. After formalizing this problem, we have defined and studied in simulation two decision rules that produce two different strategies: the first one alternates between two vehicles from each side of the road, and the second one gives priority to the vehicle with the highest delay. This work has been presented in ICTAI'12 [29] .
We are now considering more complex situations, e.g., when multiple flows of vehicles share more than one crossroad.
Multi-robot exploration and mapping : The Carotte Challenge
Participants : Olivier Simonin, François Charpillet, Antoine Bautin, Nicolas Beaufort.
In the context of the ANR/DGA Carotte Challenge, we study since 2009 new strategies and algorithms for multi-robot exploration and mapping. The proposed models are experimented with real autonomous mobile robots at LORIA and every year at the Carotte challenge. Our consortium, called “Cart-o-matic”, is composed of members from Université d'Angers (LISA) and from Maia team-project (our industrial partner has left the consortium in 2011).
The year 2012 produced several results :
In June, we won the final edition of the Carotte challenge ! This result was obtained in particular by the efficiency and the robustness of the multi-robot strategy we proposed. Our system also provided one of the best map of the contest.
We developed a software platform, including SLAM, Planning and multi-robot explorations algorithms. These softwares have been protected by copyrights (APP), see 5.4 .
We presented the results in different publications : RIA revue [8] , ICIRA'2012 International Conference [10] (Finalist for the Best student paper).
Antoine Bautin wrote his PhD thesis, that he will defend in the beginning of year 2013. This work proposes new frontier assignation algorithms for multi-robot exploration. We defined a new heuristics, based on counting the robots towards a frontier rather than considering only the distance between robots and frontiers. For these purpose we developed algorithms based on wavefronts computations (artificial potential fields).We measured on benchmarks that our algorithm outperforms the two classical approaches closest frontier and Greedy assignation.
In Oct. 2012, Nassim Kaldé started a PhD thesis (MENRT scholarship), advised by F. Charpillet and O. Simonin. We aim at continuing the work of the Cartomatic project, under new hypothesis and constrains on communications and complexity of the environment to explore.
Intelligent environments and health assistance
Spatial computing: iTiles network
Participants : Olivier Simonin, François Charpillet, Lionel Havet, Mihai Andries.
Olivier Rochel (Inria research engineer, SED Nancy) is an external collaborator.
In the context of ambient intelligence and robotic assistance, we explore the definition of an active floor composed of connected nodes, forming a network of cells. We consider different way of computation, as spatial calculus, to define robust and self-adaptive functions in the environment. We aim at dealing with walk analysis, surveillance of people activity (actimetry) and assistance (control of assistant robots, etc.).
This work can be summarized in several points :
We asked Hikob company to design the iTile model we defined at the end of year 2011. In 2012, a network of 90 iTiles has been installed on the floor of the smart apartment of the center. This apartment is an experimental platform developed in the context of the “Situated Computer Science” Action of the CPER MISN (Lorraine region, Inria and government fundings). See InfoSitu .
Each iTile is composed of one node connected to embedded sensors and to its neighboring tiles. A tile holds 4 weight sensors, an accelerometer and 16 LEDs. A simulator of the iTile network has been developed by Olivier Rochel. This tools makes easier the development on the real tiles.
Several functions have been developed and are currently under experiments: (i) detection of a person walking on the floor (ii) tracking of feet position (iii) propagation and display of information in the network.
We are involved since 2010 in the PAL Inria large scale initiative (Personally Assisted Living). In this context, Mihai Andries started a PhD thesis in oct. 2012 (funded by Inria-PAL). This PhD. aims at studying the iTiles model and its possibility for assistance functions. We also study models allowing robots to interact and to use the iTile network.
Center of pressure and Step Detection of a person walking on our intelligent floor
Participants : Amandine Dubois, François Charpillet.
It is quite easy to estimate in realtime the center of pressure of a person walking on the intelligent floor described above. From a sequence of center of pressure, we conceived a system categorizing the set of measures into two sets :
foot: the measure belongs to the pressure trace left by a foot on the floor,
transition: the center of pressure corresponds to what happens when the person passes his right leg or left from backwards to forwards.
This has been done in a first time using an heuristic algorithm and then using an HMM. From this categorization it's then easy to estimate classical gait parameters such as length of the steps or speed of the walk.
Pose estimation of several kinects
Participants : Nicolas Beaufort, François Charpillet.
Tracking one or several persons using several Kinects required to solved the calibration, i.e estimation of the pose of each kinect in the scene, knowing that the area covered by each Depth camera don't overlap with other (because of interference). We have addressed this issue using a SLAM approach implemented within a GPU.
Fall prevention and Fall detection
Participants : Amandine Dubois, François Charpillet.
A major problem of public health is the loss of autonomy of elderly people usually caused by the falls. Since 2003 one of the goal of MAIA team is to develop a system allowing to detect falls and also to analyze the gait deterioration to prevent falls. A first approach consisted in developing a markerless human motion capture system estimating the 3D positions of the body joints over time. This system used a dynamic Bayesian network and a factored particle filtering algorithm. Since 2011, we used a new approach using Microsoft Kinect camera which allows to acquire at the same time a RGB and a depth image to deal of the problem of the gait. After the extraction of the human from the background, we calculate the gait parameters from the center of mass of a person. Some parameters, as the length and the time of steps, the speed of the gait, allow to predict a deterioration of the gait of a person and an increase of the risk of falls [17] .
Another use of the extraction of center of mass of a person from the Kinect camera is to determine the activity of a person. The method uses a Hidden Markov Model to distinguish eight activities of the daily life (sitting, walking, lying (on a couch, on a bed), lying down, falling, going up on the obstacles, squatting and bending). We set up an experiment in a smart room to validate our results. Concerning the gait parameters we compare them to the real values obtained making the young subjects wake with pads soaked with ink under the shoes on the paper. The results show that there is a difference of 3-4cm between length provided by our Kinect algorithm and the real length provided by the paper. Concerning the detection of the activity, we ask to 28 subjects to perform eight situations (corresponding to the eight states of the HMM). The results showed that each situation is recognized exept “bending”, falls are detected correctly and there are no false positives except “sitting” and “qqsquatting” which are detected instead of “bending”.