Biomimetic-Based Output Feedback for Attitude Stabilization of Rigid Bodies: Real-Time Experimentation on a Quadrotor

International audienceThe present paper deals with the development of bounded feedback control laws mimicking the strategy adopted by flapping flyers to stabilize the attitude of systems falling within the framework of rigid bodies. Flapping flyers are able to orient their trajectory without any knowledge of their current attitude and without any attitude computation. They rely on the measurements of some sensitive organs: halteres, leg sensilla and magnetic sense, which give information about their angular velocity and the orientation of gravity and magnetic field vectors. Therefore, the proposed feedback laws are computed using direct inertial sensors measurements, that is vector observations with/without angular velocity measurements. Hence, the attitude is not explicitly required. This biomimetic approach is very simple, requires little computational power and is suitable for embedded applications on small control units. The boundedness of the control signal is taken into consideration through the design of the control laws by saturation of the actuators' input. The asymptotic stability Micromachines 2015, 6 994 of the closed loop system is proven by Lyapunov analysis. Real-time experiments are carried out on a quadrotor using MEMS inertial sensors in order to emphasize the efficiency of this biomimetic strategy by showing the convergence of the body's states in hovering mode, as well as the robustness with respect to external disturbances

FREQUENCY DOMAIN CHARACTERIZATION OF OPTIC FLOW AND VISION-BASED OCELLAR SENSING FOR ROTATIONAL MOTION

The structure of an animal’s eye is determined by the tasks it must perform. While vertebrates rely on their two eyes for all visual functions, insects have evolved a wide range of specialized visual organs to support behaviors such as prey capture, predator evasion, mate pursuit, flight stabilization, and navigation. Compound eyes and ocelli constitute the vision forming and sensing mechanisms of some flying insects. They provide signals useful for flight stabilization and navigation. In contrast to the well-studied compound eye, the ocelli, seen as the second visual system, sense fast luminance changes and allows for fast visual processing. Using a luminance-based sensor that mimics the insect ocelli and a camera-based motion detection system, a frequency-domain characterization of an ocellar sensor and optic flow (due to rotational motion) are analyzed. Inspired by the insect neurons that make use of signals from both vision sensing mechanisms, advantages, disadvantages and complementary properties of ocellar and optic flow estimates are discussed

Motion planning for coverage with vision-inspired sensors

In this work, we address the problem of deploying a team of mobile sensing agents for monitoring a 3-D structure. A function for measuring the quality of the vision is defined and we use a line search method for optimizing the pose of single sensors. The algorithm is extended for collaborative coverage, exploiting intermittent communication between pairs of agents, and enriched with a collision avoidance method. All the proposed algorithms are tested in simulations and real-word aerial robot

Attitude Stabilization of a Biologically Inspired Robotic Housefly via Dynamic Multimodal Attitude Estimation

In this paper, we study sensor fusion for the attitude stabilization of micro aerial vehicles, particularly mechanical flying insects. Following a geometric approach, a dynamic observer is proposed that estimates attitude based on kinematic data available from different and redundant bioinspired sensors such as halteres, ocelli, gravitometers, magnetic compass and light polarization compass. In particular, the traditional structure of complementary filters, suitable for multiple sensor fusion, is specialized to the Lie group of rigid-body rotations SO(3). The filter performance based on a three-axis accelerometer and a three-axis gyroscope is experimentally tested on a 2-d.o.f. support, showing its effectiveness. Finally, attitude stabilization is proposed based on a feedback scheme with dynamic estimation of the state, i.e., the orientation and the angular velocity. Almost-global stability of the proposed controller in the case of dynamic state estimation is demonstrated via the separation principle, and realistic numerical simulations with noisy sensors and external disturbances are provided to validate the proposed control scheme