Optical Flow Sensor Research Articles

Hot Cavity Optical Fiber Fabry–Perot Interferometer as a Flow Sensor With Temperature Self-Calibrated

An optical fiber flow sensor is developed based on a hot cavity fiber Fabry–Perot (F-P) interferometer formed by a pair of fiber Bragg gratings (FBG). Part of the F-P cavity is made up by a short (2 mm) cobalt-doped fiber (CDF). The CDF can be heated up by a heating laser so that the effective optical path length of the cavity increases. The fluid flow can take some heat away depending on the flow rate and also changes the resonant wavelength of the F-P cavity. The FBG spectrum is recovered by fitting the envelope of the F-P spectrum. The generated heat is centralized inside the cavity and could hardly influence the FBG. As the F-P and FBG are with the same sensitivity to the environment temperature, the recovered Bragg wavelength can be used as a perfect reference for the self-calibration of the temperature.

A Model-aided Optical Flow/Inertial Sensor Fusion Method for a Quadrotor

In this paper, a fault-tolerant velocity estimation method is proposed for quadrotors in a GPS denied environment. A novel filter is developed in light of the quadrotor model and measurements from optical flow and inertial sensors. The proposed filter is capable of detecting and isolating the optical flow sensor faults, by which the velocity estimation accuracy and stability will be improved. It is also demonstrated that the wind velocity is observable in the proposed filter. Therefore, the new filter can also be implemented in a windy environment, which is a significant improvement to the previous model-aided inertial sensor estimator. At the end, some simulations are carried out to verify the advantages of our method.

Autopilot for Landing Small Fixed-Wing Unmanned Aerial Vehicles with Optical Sensors

An autopilot for landing fixed-wing mini-unmanned aerial vehicles is presented in this paper. The objective was to land at a site, which is defined by three artificial visual markers placed by the operator in a triangular shape. Therefore, the landing can be realized without any map data or previously measured landing coordinates, as well as in the absence of Global Positioning System measurements. A visual-servoing controller has been developed, which uses direct feedback from, at minimum, an inertial navigation system, an airspeed sensor, and camera-image features. The image features are used to reconstruct the approach-path deviations based on the defined triangular marker geometry. The visual-servoing controller is based on strong linearizations, while at the same time being robust, simple to implement, and sufficiently accurate. In the final stage of the landing, the base markers of the triangle leave the camera’s field of view. A single optical marker and two optical-flow sensors are applied to control the touchdown phase. The proposed configuration of the flow sensors and the use of the sensor’s inherent nonlinearity lead to a simple but effective controller for a coordinated roundout and touchdown relative to the true ground. Flight-test results show the feasibility of the presented method, which can be realized with relatively low additional payload and power budget constraints and moderate computational effort.

Examining The Validity Of Fitbit Charge HR For Measuring Heart Rate In Free-living Conditions

Optical blood flow sensors (i.e. photoplethysmographic techniques) have recently been utilized in wearable activity trackers. The Fitbit Charge HRTM (FBHR) is one of the widely recognized wearable activity trackers that utilizes Fitbit’s proprietary PurePulse optical heart rate (HR) technology to automatically measure wrist-based HR. Despite its increasing popularity, however, no study to date has addressed the validity of FBHR for measuring HR in free-living conditions. PURPOSE: The purpose of this study was to examine the validity of FBHR for measuring HR using a chest strap Polar HR monitor (PHR) as a reference measure in free-living conditions. METHODS: Ten healthy college students (8 males; mean age = 26.5 ± 5.4 years; mean body mass index (BMI) = 24.5 ± 3.23 kg·m2) participated in the study. The participants were asked to perform normal daily activities for 8 hours in a day while wearing the PHR (model RS400) on their chest and two FBHRs on their dominant and non-dominant wrists, respectively. HR was recorded every minute and the minute-by-minute HR data from each monitor were synchronized by time of day. Pearson correlation was used to examine the linearity of average beats-per-minute (bpm) estimated from FBHRs with respect to the PHR. Mean differences in average bpm between the monitors were examined by a general linear model for repeated measures. Lastly, mean absolute percentage error (MAPE) of minute-by-minute bpm estimated from the FBHRs were calculated against the PHR. RESULTS: Average HRs (mean ± SD) for PHR, FBHR non-dominant, and FBHR dominant were 75.6 ± 18.5 bpm, 72.8 ± 16.7 bpm, and 73.9 ± 17.06 bpm, respectively. Pearson correlation coefficients (r) between the PHR and FBHR non-dominant and dominant were r=.805 and r=.793, respectively. MAPE were 9.17 ± 10.9% for FBHR non-dominant and 9.71 ± 12.4% for FBHR HR dominant. ANOVA and post-hoc analyses with Bonferroni revealed significant differences in estimating HR from FBHR non-dominant wrist (p=.001) and FBHR dominant wrist (p=.001) compared to PHR monitor. CONCLUSION: The results indicated that the wrist-oriented Fitbit Charge HRTM device does not provide an accurate measurement of HR during free-living condition in this study. However, further research is needed to validate these monitors with a larger sample with different population groups.

Silicon-based guided-wave optical flow sensor using a diaphragm with a small opening as an orifice

Our proposed silicon-based guided-wave optical flow sensor consists of a diaphragm with a small opening used as an orifice and a waveguide across the diaphragm. The sensor operates based on Bernoulli’s theorem and the elasto-optic effect. A sensor, which had a 10×10-mm 2 , 50- μ m -thick diaphragm with a 0.34 × 0.34-mm 2 opening, was fabricated to demonstrate and confirm the sensor operation. Measured output power as a function of flow rate using oxygen gas agreed quite well with the theoretical prediction although slight deviation was seen in the high flow rate region. Moreover, according to Bernoulli’s theorem, sensitivity is strongly dependent on sectional area of opening. So, three sensors with different opening areas, such as 0.28 × 0.28 , 0.34 × 0.34 , and 0. 55× 0.55 mm 2 , were fabricated to examine such a dependence, which would be helpful to design the sensor. The measured sensitivity was found to be almost proportional to area of the opening, similar to the theoretical prediction.

Experimental Characterization of the Twin-Eye Laser Mouse Sensor

This paper proposes the experimental characterization of a laser mouse sensor used in some optical mouse devices. The sensor characterized is called twin-eye laser mouse sensor and uses the Doppler effect to measure displacement as an alternative to optical flow-based mouse sensors. The experimental characterization showed similar measurement performances to optical flow sensors except in the sensitivity to height changes and when measuring nonlinear displacements, where the twin-eye sensor offered better performance. The measurement principle of this optical sensor can be applied to the development of alternative inexpensive applications that require planar displacement measurement and poor sensitivity toz-axis changes such as mobile robotics.

A method for ego-motion estimation in micro-hovering platforms flying in very cluttered environments

We aim at developing autonomous miniature hovering flying robots capable of navigating in unstructured GPS-denied environments. A major challenge is the miniaturization of the embedded sensors and processors that allow such platforms to fly by themselves. In this paper, we propose a novel ego-motion estimation algorithm for hovering robots equipped with inertial and optic-flow sensors that runs in real-time on a microcontroller and enables autonomous flight. Unlike many vision-based methods, this algorithm does not rely on feature tracking, structure estimation, additional distance sensors or assumptions about the environment. In this method, we introduce the translational optic-flow direction constraint, which uses the optic-flow direction but not its scale to correct for inertial sensor drift during changes of direction. This solution requires comparatively much simpler electronics and sensors and works in environments of any geometry. Here we describe the implementation and performance of the method on a hovering robot equipped with eight 0.65 g optic-flow sensors, and show that it can be used for closed-loop control of various motions.

Motion control of an omnidirectional climbing robot based on dead reckoning method

While omnidirectional wheels enable a holonomic drive and a good maneuverability, the slippage of the wheels as an inherent characteristic of the omnidirectional wheels prevents using rotary shaft encoders as a reliable source of data for the robot’s odometry. When installed on a climbing robot, omnidirectional wheels may suffer from additional slippage on the surface. In a previous study, we described how the resulting vibration decreases the trajectory following accuracy of the robot, and why rotary encoders, as the most popular dead reckoning method cannot be used. In this paper, we address this problem by integration of low cost and light weight exteroceptive sensors, i.e. an accelerometer and an optical flow sensor. The Omniclimber climbing robot was used as the testing platform in this study. Omniclimbers are omnidirectional climbing robots that can climb and navigate over flat and curved structures. We attempt to compensate the errors due to the wheel slippage through closing the position control loop without significantly increasing the robot’s weight, cost and complexity of the robot. We also integrated an algorithm which corrects the robot kinematics on the curved structures based on the curvature diameter and the robot’s heading angle. Taking advantage of these sensors and algorithms we could make remarkable improvements on the path following accuracy of the Omniclimbers, which is presented in this article.

Bioinspired Navigation for a Nonholonomic Mobile Robot

This work addresses the problem of navigation of an autonomous flying vehicle using an optic flow sensing approach motivated by the visuomotor system of insects. Here, the state estimation and conflict resolution aspects of this problem are considered. Specifically, the observability of the robot with an arbitrary number of sensors is investigated, and the minimum number of optic flow sensors and the sensor configuration necessary to have an observable system are determined. The system dynamics linearized about a point are not observable, but a nonlinear observability analysis based on Lie derivatives indicates that the sensor measurements provide enough information for estimating the states of the system. A control policy that guarantees a conflict-free path is also described. In this work, planar obstacles are considered, such as walls. The results are demonstrated in simulation.

Afocal optical flow sensor for reducing vertical height sensitivity in indoor robot localization and navigation.

This paper introduces a novel afocal optical flow sensor (OFS) system for odometry estimation in indoor robotic navigation. The OFS used in computer optical mouse has been adopted for mobile robots because it is not affected by wheel slippage. Vertical height variance is thought to be a dominant factor in systematic error when estimating moving distances in mobile robots driving on uneven surfaces. We propose an approach to mitigate this error by using an afocal (infinite effective focal length) system. We conducted experiments in a linear guide on carpet and three other materials with varying sensor heights from 30 to 50 mm and a moving distance of 80 cm. The same experiments were repeated 10 times. For the proposed afocal OFS module, a 1 mm change in sensor height induces a 0.1% systematic error; for comparison, the error for a conventional fixed-focal-length OFS module is 14.7%. Finally, the proposed afocal OFS module was installed on a mobile robot and tested 10 times on a carpet for distances of 1 m. The average distance estimation error and standard deviation are 0.02% and 17.6%, respectively, whereas those for a conventional OFS module are 4.09% and 25.7%, respectively.

1 kHz 2D Visual Motion Sensor Using 20<formula formulatype="inline"><tex Notation="TeX">$\,\times\,$</tex></formula>20 Silicon Retina Optical Sensor and DSP Microcontroller

Optical flow sensors have been a long running theme in neuromorphic vision sensors which include circuits that implement the local background intensity adaptation mechanism seen in biological retinas. This paper reports a bio-inspired optical motion sensor aimed towards miniature robotic and aerial platforms. It combines a 20 × 20 continuous-time CMOS silicon retina vision sensor with a DSP microcontroller. The retina sensor has pixels that have local gain control and adapt to background lighting. The system allows the user to validate various motion algorithms without building dedicated custom solutions. Measurements are presented to show that the system can compute global 2D translational motion from complex natural scenes using one particular algorithm: the image interpolation algorithm (I2A). With this algorithm, the system can compute global translational motion vectors at a sample rate of 1 kHz, for speeds up to ±1000 pixels/s, using less than 5 k instruction cycles (12 instructions per pixel) per frame. At 1 kHz sample rate the DSP is 12% occupied with motion computation. The sensor is implemented as a 6 g PCB consuming 170 mW of power.

Flying over uneven moving terrain based on optic-flow cues without any need for reference frames or accelerometers

Two bio-inspired guidance principles involving no reference frame are presented here and were implemented in a rotorcraft, which was equipped with panoramic optic flow (OF) sensors but (as in flying insects) no accelerometer. To test these two guidance principles, we built a tethered tandem rotorcraft called BeeRotor (80 grams), which was tested flying along a high-roofed tunnel. The aerial robot adjusts its pitch and hence its speed, hugs the ground and lands safely without any need for an inertial reference frame. The rotorcraft’s altitude and forward speed are adjusted via two OF regulators piloting the lift and the pitch angle on the basis of the common-mode and differential rotor speeds, respectively. The robot equipped with two wide-field OF sensors was tested in order to assess the performances of the following two systems of guidance involving no inertial reference frame: (i) a system with a fixed eye orientation based on the curved artificial compound eye (CurvACE) sensor, and (ii) an active system of reorientation based on a quasi-panoramic eye which constantly realigns its gaze, keeping it parallel to the nearest surface followed. Safe automatic terrain following and landing were obtained with CurvACE under dim light to daylight conditions and the active eye-reorientation system over rugged, changing terrain, without any need for an inertial reference frame.

Obstacle Detection and Collision Avoidance for a UAV With Complementary Low-Cost Sensors

This paper demonstrates an innovative and simple solution for obstacle detection and collision avoidance of unmanned aerial vehicles (UAVs) optimized for and evaluated with quadrotors. The sensors exploited in this paper are low-cost ultrasonic and infrared range finders, which are much cheaper though noisier than more expensive sensors such as laser scanners. This needs to be taken into consideration for the design, implementation, and parametrization of the signal processing and control algorithm for such a system, which is the topic of this paper. For improved data fusion, inertial and optical flow sensors are used as a distance derivative for reference. As a result, a UAV is capable of distance controlled collision avoidance, which is more complex and powerful than comparable simple solutions. At the same time, the solution remains simple with a low computational burden. Thus, memory and time-consuming simultaneous localization and mapping is not required for collision avoidance.

Research on a novel variable-area optical fiber gas flow sensor

Based on the structure of the traditional variable area flow meter and the principle of the optical fiber measurement, this article designed a new type of fiber Bragg grating (FBG) gas flow sensor. The tapered tube of the sensor is mounted vertically, and the float inside the tube moves up and down under the effect of the airflow. The longitudinal displacement of the float is converted to the deflection of the cantilever which bonded FBG under the action of magnetic force. Thus the flow variation could be transformed into the deflection of the cantilever, resulting in the change of FBG wavelength and phase. By detecting the change of the optical signal, the gas flow can be derived. The experimental results show that the sensor has the characteristics of good linearity and fast response time. The proposed sensor can determine the flow of air within 1–6.5m3/h and the sensitivity of the sensor approximately reaches 0.22nm/(m3/h). By optimizing the parameters of the sensor, the sensitivity and the accuracy can be improved accordingly.

Fiber loop ringdown gas flow sensors

Fiber loop ringdown (FLRD) is a versatile sensing technique, which has been increasingly used for the development of high sensitivity, fast response FLRD chemical, physical, and biomedical sensors. In this paper, we report the first fiber loop ringdown gas flow sensor. The FLRD gas flow sensor is based on a micro-bending sensing mechanism, in which optical loss is induced when a gas flows through the sensor head and creates a physical deformation. The sensor was employed to determine airflow at various rates. Two different sensor head configurations were investigated. The results show that the sensor has a high upper measuring range of 5–22.5 standard liters per minute (slpm). Given the known airflow cross sections used, the corresponding airflow speeds measured in this work are within the range of 5.7–311.0 m s−1. A theoretical detection resolution limit (minimum detectable change) for the sensor is estimated to be 0.1 slpm using the best fiber loop ringdown baseline stability of 0.2%, while the experimentally measured resolution limit is 2.5 slpm (or 2.9 m s−1). The sensor demonstrated a fast response (<1 s) and excellent reproducibility and reversibility. Compared with other types of airflow fiber optic sensors, this new FLRD airflow sensor, besides its simplicity and low cost, offers the additional capability of measuring higher gas flow rates and a high potential for the fiber optic gas flow sensor network.

Bio-inspired modeling and implementation of the ocelli visual system of flying insects.

Two visual sensing modalities in insects, the ocelli and compound eyes, provide signals used for flight stabilization and navigation. In this article, a generalized model of the ocellar visual system is developed for a 3-D visual simulation environment based on behavioral, anatomical, and electrophysiological data from several species. A linear measurement model is estimated from Monte Carlo simulation in a cluttered urban environment relating state changes of the vehicle to the outputs of the ocellar model. A fully analog-printed circuit board sensor based on this model is designed and fabricated. Open-loop characterization of the sensor to visual stimuli induced by self motion is performed. Closed-loop stabilizing feedback of the sensor in combination with optic flow sensors is implemented onboard a quadrotor micro-air vehicle and its impulse response is characterized.

Design of Quadrotor’s Control System Based on DSP

A problem of quadrotor’s control system based on DSP is investigated in this paper. STMS320F28335 is used as the main processer, due to its advantages of high-speed processing capability and powerful floating point processing capability. The inertial measurement unit is selected for inner-loop attitude control, while the optical flow sensor is adopted for outer-loop attitude compensation. Infrared range finder is choosed for altitude control with PID method. Quadrotor uses XBee-Pro wireless module to contact with ground station and sends statement information in accordance with the Mavlink protocol. Test results show that the control system is reliable and can meet the requirement of the attitude control system.

Autonomous Visual Mapping and Exploration With a Micro Aerial Vehicle

Cameras are a natural fit for micro aerial vehicles (MAVs) due to their low weight, low power consumption, and two‐dimensional field of view. However, computationally‐intensive algorithms are required to infer the 3D structure of the environment from 2D image data. This requirement is made more difficult with the MAV's limited payload which only allows for one CPU board. Hence, we have to design efficient algorithms for state estimation, mapping, planning, and exploration. We implement a set of algorithms on two different vision‐based MAV systems such that these algorithms enable the MAVs to map and explore unknown environments. By using both self‐built and off‐the‐shelf systems, we show that our algorithms can be used on different platforms. All algorithms necessary for autonomous mapping and exploration run on‐board the MAV. Using a front‐looking stereo camera as the main sensor, we maintain a tiled octree‐based 3D occupancy map. The MAV uses this map for local navigation and frontier‐based exploration. In addition, we use a wall‐following algorithm as an alternative exploration algorithm in open areas where frontier‐based exploration under‐performs. During the exploration, data is transmitted to the ground station which runs large‐scale visual SLAM. We estimate the MAV's state with inertial data from an IMU together with metric velocity measurements from a custom‐built optical flow sensor and pose estimates from visual odometry. We verify our approaches with experimental results, which to the best of our knowledge, demonstrate our MAVs to be the first vision‐based MAVs to autonomously explore both indoor and outdoor environments.

Small Brains, Smart Machines: From Fly Vision to Robot Vision and Back Again

Neurobiological and neuroethological findings on insects can be used to design and construct small robots controlling their navigation on the basis of bio-inspired visual strategies and circuits. Animals' visual guidance is partly mediated by motion-sensitive neurons, which are responsible for gauging the optic flow. Although neurons of this kind were discovered in vertebrates' and invertebrates' visual systems more than 50 years ago, the principles and neural mechanisms involved have not yet been completely elucidated. Here, first, I propose to outline some of the findings we made during the last few decades by performing electrophysiological recordings on identified neurons in the housefly's eye while applying optical stimulation to identified photoreceptors. Whereas these findings shed light on the inner processing structure of an elementary motion detector (EMD), recent studies in which the latest genetic and neuroanatomical methods were applied to the fruitfly's visual system have identified some of the neurons in the visual chain which are possibly involved in the neural circuitry underlying a given EMD. Then, I will describe some of the proof-of-concept robots that we have developed on the basis of our biological findings. The 100-g robot OCTAVE, for example, is able to avoid the ground, react to wind, and land autonomously on a flat terrain without ever having to measure any state variables such as distances or speeds. The 100-g robots OSCAR 1 and OSCAR 2 inspired by the microscanner we discovered in the housefly's eye are able to stabilize their body using mainly visual means and track a moving edge with hyperacuity. These robots react to the optic flow, which is sensed by miniature optic flow sensors inspired by the housefly's EMDs. Constructing a “biorobot” gives us a unique opportunity of checking the soundness and robustness of a principle that is initially thought to be understood by bringing it face to face with the real physical world. Bio-inspired robotics not only help neurobiologists and neuroethologists to identify and investigate worthwhile problems in animals' sensory-motor systems, but they also provide engineers with ideas for developing novel devices and machines with promising future applications, in the field of smart autonomous vehicles and microvehicles, for example.

Efficient Hardware Implementation of the Horn-Schunck Algorithm for High-Resolution Real-Time Dense Optical Flow Sensor

This article presents an efficient hardware implementation of the Horn-Schunck algorithm that can be used in an embedded optical flow sensor. An architecture is proposed, that realises the iterative Horn-Schunck algorithm in a pipelined manner. This modification allows to achieve data throughput of 175 MPixels/s and makes processing of Full HD video stream (1, 920 × 1, 080 @ 60 fps) possible. The structure of the optical flow module as well as pre- and post-filtering blocks and a flow reliability computation unit is described in details. Three versions of optical flow modules, with different numerical precision, working frequency and obtained results accuracy are proposed. The errors caused by switching from floating- to fixed-point computations are also evaluated. The described architecture was tested on popular sequences from an optical flow dataset of the Middlebury University. It achieves state-of-the-art results among hardware implementations of single scale methods. The designed fixed-point architecture achieves performance of 418 GOPS with power efficiency of 34 GOPS/W. The proposed floating-point module achieves 103 GFLOPS, with power efficiency of 24 GFLOPS/W. Moreover, a 100 times speedup compared to a modern CPU with SIMD support is reported. A complete, working vision system realized on Xilinx VC707 evaluation board is also presented. It is able to compute optical flow for Full HD video stream received from an HDMI camera in real-time. The obtained results prove that FPGA devices are an ideal platform for embedded vision systems.