Marc Boyron

A novel 1-gram insect based device measuring visual motion along 5 optical directions

Autopilots for micro aerial vehicles (MAVs) with a maximum permissible avionic payload of only a few grams need lightweight, low-power sensors to be able to navigate safely when flying through unknown environments. To meet these demanding specifications, we developed a simple functional model for an Elementary Motion Detector (EMD) circuit based on the common houseflys visual system. During the last two decades, several insect-based visual motion sensors have been designed and implemented on various robots, and considerable improvements have been made in terms of their mass, size and power consumption. The new lightweight visual motion sensor presented here generates 5 simultaneous neighboring measurements of the 1-D angular speed of a natural scene within a measurement range of more than one decade [25°/s; 350°/s]. Using a new sensory fusion method consisting in computing the median value of the 5 local motion units, we ended up with a more robust, more accurate and more frequently refreshed measurement of the 1-D angular speed.

Local Positioning System Using Flickering Infrared LEDs

A minimalistic optical sensing device for the indoor localization is proposed to estimate the relative position between the sensor and active markers using amplitude modulated infrared light. The innovative insect-based sensor can measure azimuth and elevation angles with respect to two small and cheap active infrared light emitting diodes (LEDs) flickering at two different frequencies. In comparison to a previous lensless visual sensor that we proposed for proximal localization (less than 30 cm), we implemented: (i) a minimalistic sensor in terms of small size (10 cm3), light weight (6 g) and low power consumption (0.4 W); (ii) an Arduino-compatible demodulator for fast analog signal processing requiring low computational resources; and (iii) an indoor positioning system for a mobile robotic application. Our results confirmed that the proposed sensor was able to estimate the position at a distance of 2 m with an accuracy as small as 2-cm at a sampling frequency of 100 Hz. Our sensor can be also suitable to be implemented in a position feedback loop for indoor robotic applications in GPS-denied environment.

Overcoming the Variability of Fingertip Friction with Surface-Haptic Force-Feedback

Touch screens have pervaded our lives as the most widely used human-machine interface, and much research has focused recently on producing vivid tactile sensations on these flat panels. One of the main methods used for this purpose is based on ultrasonic vibration to controllably reduce the friction experienced by a finger touching a glass plate. Typically, these devices modulate the amplitude of the vibration in order to control the frictional force that the finger experiences without monitoring the actual output. However, since friction is a complex physical process, the open-loop transfer function is not stationary and varies with a wide range of external parameters such as the velocity of exploration or the ambient moisture. The novel interface we present here incorporates a force sensor which measures subtle changes of the frictional force on a wide frequency bandwidth including static forces. This force sensor is the basis for real time control of the frictional force of the finger, which reduces significantly the inherent variability of ultrasonic friction modulation while maintaining a noise level below human perception thresholds. The interface is able to render of precise and sharp frictional patterns directly on the user’s fingertip.

A novel hyperacute gimbal eye to implement precise hovering and target tracking on a quadrotor

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 robots gaze onto a target and compensate for the robots 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 eyes orientation allowed the robot to track a target moving at a speed up to 200° · s-1.

X-Morf: A crash-separable quadrotor that morfs its X-geometry in flight

The X-Morf robot is a 380-g quadrotor consisting of two independent arms each carrying tandem rotors, forming an actuated scissor joint. The X-Morf robot is able to actively change in-flight its X-geometry by changing the angle between its two arms. The magnetic and electrical joint between the quadrotors arms makes them easily removable and resistant to crashes while providing the propellers with sufficient power and ensuring high quality signal transmission during flight. The dynamic model on which the X-Morf robot was based, was also used to design an adaptive controller. A Model Reference Adaptive Control (MRAC) law was implemented to deal with the uncertainties about the inertia and the center of mass due to the quadrotors reconfigurable architecture and for in-flight span-adapting purposes. The tests performed with the X-Morf robot showed that it is able to decrease and increase its span dynamically by up to 28.5% within 0.5s during flight while giving good stability and attitude tracking performances.