International audience

Uncertainty estimation of visual feature is essential for vision-based systems, such as visual navigation. We show that errors inherent to visual tracking, in particular using KLT tracker, can be learned using a probabilistic loss function to estimate the covariance matrix on each tracked feature position. The proposed system is trained and evaluated on synthetic data, as well as on real data, highlighting good results in comparison to the state of the art. The benefits of the tracking uncertainty estimates are illustrated for visual motion estimation.

This paper investigates the trajectory generation problem for a fleet of Unmanned Aerial Vehicles (UAVs) performing escort missions with respect to a convoy with a time-varying velocity. Using camera-equipped UAVs, we propose a framework allowing to adapt the UAVs altitudes to achieve a trade-off between the size of the covered surface and the image resolution by solving an optimization problem. Furthermore, we perform polynomial refinement based on the generated planar way-points to yield a minimum-jerk time-parameterized trajectory with dynamical constraints on the virtual leader to follow. The numerical simulations presented in this paper show the effectiveness of the optimization algorithm in adapting the UAVs altitudes to satisfy a compromise between the size of the covered area and its corresponding image resolution.

This paper proposes a trajectory generation strategy of quadcopter formation for area surveillance and inspection using multiple cameras. The proposed technique exploits a minimal virtual-leader based network topology to generate the executable trajectories where generating trajectories for each agent is no longer necessary. A coverage path planning algorithm is employed to generate a set of planar waypoints, which are then optimised to yield a minimum-jerk time-parametrised trajectory with dynamical constraints of the virtual leader to follow. In order to establish a formation pattern, the desired distance among the agents is then computed based on the operation mode, size of the area to cover, and the number of deployed UAVs. Numerical simulations demonstrate the effectiveness of the proposed method.

The widespread use of mobile devices and location-based services has generated a large number of mobility databases. While processing these data is highly valuable, privacy issues can occur if personal information is revealed. The prior art has investigated ways to protect mobility data by providing a wide range of Location Privacy Protection Mechanisms (LPPMs). However, the privacy level of the protected data significantly varies depending on the protection mechanism used, its configuration and on the characteristics of the mobility data. Meanwhile, the protected data still needs to enable some useful processing. To tackle these issues, we present PULP, a framework that finds the suitable protection mechanism and automatically configures it for each user in order to achieve user-defined objectives in terms of both privacy and utility. PULP uses nonlinear models to capture the impact of each LPPM on data privacy and utility levels. Evaluation of our framework is carried out with two protection mechanisms from the literature and four real-world mobility datasets. Results show the efficiency of PULP, its robustness and adaptability. Comparisons between LPPMs' configurators and the state of the art further illustrate that PULP better realizes users' objectives, and its computation time is in orders of magnitude faster.

Nowadays, the market of Unmanned Aerial Systems (UAS) develops progressively with a lot of applications such as: infrastructure monitoring, law enforcement, environment research, goods transportation, etc. However, due to the lack of human observation, communication capacities, and protection, a UAS is an appropriate target for a criminal or a terrorist cyber attack. Therefore, risks related to the cyber-security need to be taken into account during the development of a UAS. This document presents a risk management methodology related to cyber-security. The expected result of the application of this methodology is a list of cyber-security requirements which guides the development of cyber-security countermeasures.

This video presents a distributed trajectory generator for formation control of multi-robot systems. The desired formation is defined by its geometric parameters but the position of each robot in the formation is not predefined a priori. The contribution is the design of a distributed algorithm to compute the robots' positions with respect to a given target while maintaining a particular formation which can be reconfigured on-line. A tracking controller ensures the convergence of the robots to their desired positions.

Companies have a fast growing amounts of data to process and store, a data explosion is happening next to us. Currently one of the most common approaches to treat these vast data quantities are based on the MapReduce parallel programming paradigm. While its use is widespread in the industry, ensuring performance constraints, while at the same time minimizing costs, still provides considerable challenges. We propose a coarse grained control theoretical approach, based on techniques that have already proved their usefulness in the control community. We introduce the first algorithm to create dynamic models for Big Data MapReduce systems, running a concurrent workload. Furthermore, we identify two important control use cases: relaxed performance-minimal resource and strict performance. For the first case we develop two feedback control mechanism. A classical feedback controller and an even-based feedback, that minimises the number of cluster reconfigurations as well. Moreover, to address strict performance requirements a feedforward predictive controller that efficiently suppresses the effects of large workload size variations is developed. All the controllers are validated online in a benchmark running in a real 60 node MapReduce cluster, using a data intensive Business Intelligence workload. Our experiments demonstrate the success of the control strategies employed in assuring service time constraints.

This work uses the intermediary quaternions in the design of a backstepping control technique with integral properties in order to perform an autonomous trajectory tracking using a quadcopter vehicle. Nowadays, in order to determine the orientation of a vehicle, most of the inertial systems of aircrafts can give directly the rotation matrix and taking advantage of this fact, the intermediary quaternions can be determined in a simple way from this matrix. Moreover, one specific orientation corresponds to only one intermediary quaternion and this helps to cope the unwinding phenomenon presented when working with the classical quaternions. The proposed control algorithm is validated numerically and experimentally when the quadrotor follows a circular trajectory. In addition, during the simulation part, some external perturbations and white noise were added in order to test the robustness of the algorithm.

Leveraging location information in location-based services leads to improving service utility through geocontextualization. However, this raises privacy concerns as new knowledge can be inferred from location records, such as user's home and work places, or personal habits. Although Location Privacy Protection Mechanisms (LPPMs) provide a means to tackle this problem, they often require manual configuration posing significant challenges to service providers and users. Moreover, their impact on data privacy and utility is seldom assessed. In this paper, we present PULP, a model-driven system which automatically provides user-specific privacy protection and contributes to service utility via choosing adequate LPPM and configuring it. At the heart of PULP is nonlinear models that can capture the complex dependency of data privacy and utility for each individual user under given LPPM considered, i.e., Geo-Indistinguishability and Promesse. According to users' preferences on privacy and utility, PULP efficiently recommends suitable LPPM and corresponding configuration. We evaluate the accuracy of PULP's models and its effectiveness to achieve the privacy-utility trade-off per user, using four real-world mobility traces of 770 users in total. Our extensive experimentation shows that PULP ensures the contribution to location service while adhering to privacy constraints for a great percentage of users, and is orders of magnitude faster than non-model based alternatives.

This paper presents a new minimalist bio-inspired artificial eye of only 24 pixels, able to locate accurately a target placed in its small field of view (±10°). The eye is mounted on a very light custom-made gimbal system which makes the eye able to track faithfully a moving target. We have shown, that our gimbal eye can be embedded on a small quadrotor to achieve accurate hovering with respect to a target placed onto the ground. Our aiborne eye was enhanced with a bio-inspired reflex in charge of locking efficiently the robot's gaze onto a target and compensate for the robot's rotations and disturbances. The use of very few pixels allowed to implement a visual processing algorithm at a refresh rate of 400 Hz. This high refresh rate coupled to a very fast control of the eye's orientation allowed the robot to track a target moving at a speed up to 200° · s-1.

This paper proposes a simple solution for stabilization of a nano-hexacopter carrying a manipulator arm in order to increase the type of missions achievable by these types of systems. The manipulator arm is attached to the lower part of the hexacopter. The motion of the arm induces a change of the center of mass of the whole body, which induces torques which can produce the loss of stability. The present work deals with the stabilization of the whole system - that is hexacopter and arm - by means of a set of nonlinear control laws. First, an attitude control, stabilizes the hexacopter to a desired attitude taking into account the movement of the arm. Then, a suitable virtual control and the translational dynamics allow the formulation of a nonlinear controller, which drives the aerial vehicle to a desired position. Both controls consist in saturation functions. Experimental results validate the proposed control strategy and compares the results when the motion of the arm is taken into account or not.

In this paper, a state-feedback linear-quadratic regulator (LQR) is proposed for event-based control of a linear system. An interesting property of LQRs is that an optimal response of the system can be obtained in accordance to some specifications, like the actuator limits. An integral action is also added in order to not only restrict the study to null stabilization but also to tracking. The idea is to consider an external control loop and stabilize the integral of the error between the measurement and a desired setpoint to track. However, an event-triggered integral can lead to important overshoots when the interval between two successive events becomes large. Therefore, an exponential forgetting factor of the sampling interval is proposed as a solution to avoid such problems. The whole proposal is tested on a real-time system (a gyroscope) in order to highlight its ability, the reduction of control updates and the respect to the actuator limits.

Hovering flies are capable of achieving outstanding performances when hovering above flowers for several minutes. A new insect-based hovering control strategy is presented here for accurately stabilizing the position of a sighted twin-rotor equipped with a decoupled eye with a narrow field-of-view of only a few degrees. The main aim of this paper is to describe how accurately hovering flight above a target can be achieved by means of this fundamental bio-inspired mechanical decoupling system between the eye and the body. The simulated gaze control system implemented on-board the aerial robot has several advantages : - it enables the robot's gaze to be stabilized on the basis of three bio-inspired oculomotor reflexes (ORs) : a visual fixation reflex (VFR), a translational reflex and a rotational vestibulo-ocular reflex (tVOR and rVOR), - it makes the eye compensate quickly and accurately for any sudden, untoward disturbances caused by the vagaries of the supporting head or body, - it provides a reference visual signal to compensate for the rate gyro drift used to implement the VORs and to stabilize the hovering robot, - it greatly improves the stability of the robot's roll during voluntary lateral displacements with respect to the target. Close comparisons were made between two simulated robots with and without a decoupled eye, which were both subjected to strong lateral and roll disturbances. The simulations show that the robot with a decoupled eye can reject disturbances twice as fast as that with a fixed eye. This innovative bio-inspired hovering control method stabilizes the robot's attitude without any need for accelerometers, magnetometers or classical inertial measurement units.

Server technology provides a means to support a wide range of online services and applications. However, their ad hoc configuration poses significant challenges to the performance, availability, and economical costs of applications. In this paper, we examine the impact of server configuration on the central trade-off between service performance and availability. First, we present a server model as a nonlinear continuous-time model using fluid approximations. Second, we develop concurrency control on server systems for an optimal configuration. We primarily provide two control laws for two different QoS objectives. AM-C is an availability-maximizing server control that achieves the highest service availability given a fixed performance constraint; and PM-C is a performance-maximizing control law that meets a desired availability target with the highest performance. We then improve the control with two additional multilevel laws. AA-PM-C is an availability-aware performance-maximizing control, and PA-AM-C is a performance-aware availability-maximizing control. In this paper, we present ConSer, a novel system for the control of servers. We evaluate ConSer's fluid model and control techniques on the TPC-C industry-standard benchmark. Our experiments show that the proposed techniques successfully guarantee performance and availability constraints.

Although server technology provides a means to support a wide range of online services and applications, their ad-hoc configuration poses significant challenges to the performance, availability and economical costs of applications. In this paper, we examine the impact of server configuration on the central tradeoff between service performance and availability. First, we present a server model as a nonlinear continuous-time model using fluid approximations. Second, we develop admission control of server systems for an optimal configuration. We provide two control laws for two different QoS objectives. AM-C is an availability-maximizing admission control that achieves the highest service availability given a fixed performance constraint; and PM-C is a performance-maximizing admission control that meets a desired availability target with the highest performance. We evaluate our fluid model and control techniques on the TPC-C industry-standard benchmark. Our experiments show that the proposed techniques improve performance by up to 30 % while guaranteeing availability constraints.

This paper presents two bounded attitude control laws of a high frequency Flapping Micro Aerial Vehicle (FMAV) based on sensors measurements feedback. First, a simplified model of a FMAV is proposed using only the steady aerodynamic efforts. Since solely the averaged forces and torques affect the body's movement, the control laws are computed using the averaged model and applied to the time varying model at the beginning of each wingbeat period. A first control law is developed using a rate gyro (measuring the body's angular velocity), and some reference sensors used to compute the attitude error. A second control law is proposed omitting the rate gyro in order to reduce FMAV's size and weight. The control laws are highly simple and bounded in order to prevent the saturation of the actuators and to increase their efficiency. The control strategies are compared and tested with respect to external disturbances.

This paper presents a bounded control of a flapping micro aerial vehicle (MAV) in three dimensions. First, a simplified model of the flapping MAV is presented aiming to test the control law. The averaging theory shows that for high frequency systems, only the mean aerodynamic forces and torques over a period affect the movement of the body. Therefore, a bounded nonlinear state feedback control, calculated using the averaged model, is applied to the time varying system in order to stabilize it at a desired position in hovering mode. The robustness of the control is tested with respect to the aerodynamic coefficient and to external disturbances.

In this paper, a multi-variable feedback design for the 3D movement of an eel-like robot is presented. Such a robot is under construction in the context of a national French robotic project. The proposed feedback enables the tracking of a desired 3D position of the eelpsilas head as well as the stabilization of the rolling angle. The control design is based on a recently developed reduced model that have been validated using a 3D complete continuous model described in [3]. Several scenarios are proposed to assess the efficiency of the proposed feedback law.

This paper relates recent advances in the design of feedback laws for the 3D movement of an Eel-like robot. Such a robot is under construction in the context of a national French robotic project. The proposed feedback enables the tracking of a desired 3D position of the Eel head as well as the stabilization of the rolling angle. A velocity controller is also proposed. The controller is tested on a recently developed complete 3D model in order to assess its efficiency in tackling 3D manoeuvres.

A quaternion based feedback is developed for attitude stabilization of rigid body. The control design takes into account the input bounds and is based on cascaded saturation approach. The global stability is guaranteed. A simulation study of the proposed scheme is illustrated for the four-rotor helicopter.

This paper proposes a global asymptotic stabilizing control law for a quad-rotor helicopter with bounded inputs. The proposed control design exploits the technique based on the sum of saturating functions and is based on the global stabilization of multiple integrators with bounded inputs. The positiveness of the thrust and the boundedness of the control inputs are taken into account. Numerical simulations show the effectiveness of the proposed controller.