José Luis Lázaro Galilea

Infrared Sensor System for Mobile-Robot Positioning in Intelligent Spaces

The aim of this work was to position a Mobile Robot in an Intelligent Space, and this paper presents a sensorial system for measuring differential phase-shifts in a sinusoidally modulated infrared signal transmitted from the robot. Differential distances were obtained from these phase-shifts, and the position of the robot was estimated by hyperbolic trilateration. Due to the extremely severe trade-off between SNR, angle (coverage) and real-time response, a very accurate design and device selection was required to achieve good precision with wide coverage and acceptable robot speed. An I/Q demodulator was used to measure phases with one-stage synchronous demodulation to DC. A complete set of results from real measurements, both for distance and position estimations, is provided to demonstrate the validity of the system proposed, comparing it with other similar indoor positioning systems.

Embedded Vision Modules for Tracking and Counting People

This paper shows the algorithm implementation for a field-programmable gate array (FPGA)-based design for people counting using a low-level head-detection method. The hardware (HW) implementation on an FPGA allows the capture and online processing in real time on the same chip. Different annular patterns are used to process in parallel the image and detect heads of different sizes. Preprocessing and edge extraction are also made using reconfigurable HW. The developed system exploits HW processing, as the vision algorithm has been modified and tuned for HW implementation. It uses minimal area resources of a Spartan3 (1.5 Mgates), and its real-time performance is comparable with more sophisticated algorithms while utilizing very low cost circuits.

Coverage-Mapping Method Based on a Hardware Model for Mobile-Robot Positioning in Intelligent Spaces

In this paper, we describe a method for relating the precision in phase shift measurements to the navigation areas in which that precision is reached so that a coverage map is built, setting a signal-to-noise ratio (SNR) threshold level that depends on that phase precision. The method brings a novel approach to linking different areas in robotics and is applied to a mobile-robot (MR) local positioning system (LPS) in an intelligent space, where distances are computed from differential phase shift measurements with intensity modulation and direct detection (IMDD) infrared signals. A global model including the parameters of all the parts involved, e.g., optoelectronics, wireless channel, and instrumentation hardware, is developed. Furthermore, based on the model, an analytical expression deduced for the phase shift measurement is used to find the necessary SNR for a desired precision. A complete set of results, applying the coverage cells to a real building covering a path followed by an MR, is shown. The position of the MR can be known, with an accuracy value below 5 cm and tested in a basic rectangular locating cell with dimensions 3.0 m × 2.5 m.

Calibration of a High-Accuracy 3-D Coordinate Measurement Sensor Based on Laser Beam and CMOS Camera

We present an advanced method of system calibration measurement to improve the precision in obtaining measurements of 3-D coordinates. This system is comprised of a CMOS array sensor and an infrared (IR) emitter. Improving the accuracy requires improving the method of sensor calibration. In this paper, a process of calibrating systems for geometry determination and positioning a mobile robot is developed. The system calibration method uses the perspective projection model based on the pinhole model, taking into account the intrinsic and extrinsic parameters of the camera together with the parameters of the pattern plane. We also consider the distortion effects of the lenses and the errors obtained in detection. To run the method, the applied calibration pattern is a planar surface with several circular points. The CMOS camera is equipped with a short-focal-length lens.

Guidance of Autonomous Vehicles by Means of Structured Light

Abstract This paper describes a system comprising a CCD sensor coupled with an infra-red emitter so that the emission of structured light then captured in the sensor CCD (vision angle 90°) gives the 3-D co-ordinates of the light impact points. Working from the co-ordinate matrix supplied, surrounding obstacles and vacant areas can be detected. The environment through which the robot may move is generated considering its dimensions and orientation. A check is made in the latest environment update of whether any obstacles balk the objective. If so, the path is varied so that the obstacle is avoided and the path optimum.

Improving the Calibration of Image Sensors Based on IOFBs, Using Differential Gray-Code Space Encoding

This paper presents a fast calibration method to determine the transfer function for spatial correspondences in image transmission devices with Incoherent Optical Fiber Bundles (IOFBs), by performing a scan of the input, using differential patterns generated from a Gray code (Differential Gray-Code Space Encoding, DGSE). The results demonstrate that this technique provides a noticeable reduction in processing time and better quality of the reconstructed image compared to other, previously employed techniques, such as point or fringe scanning, or even other known space encoding techniques.

Preliminary simulation for an optical-indoor positioning system based on cyclic-Time Difference of Arrival

In this contribution, a cyclic-TDOA methodology is simulated. The simulation is a preliminary study that would allow to design and to implement an indoor optical-positioning system relaxing the synchronization requirements among receivers. The synchronism requirement relaxations are carried out by the modification of the structure of the positioning system considering an emitter beacon formed with three IR emitters and a few receivers strategically placed on ceiling of the positioning cell. In other side, the signal processing scheme considers the Gardners cyclic-TDOA methods to provide higher robustness with noise and interference. The simulation demonstrated the higher performance of cyclic-TDOA over classical GCC methods, even with lowest SNR scenarios.

Decoupling Intensity Radiated by the Emitter in Distance Estimation from Camera to IR Emitter

Various models using radiometric approach have been proposed to solve the problem of estimating the distance between a camera and an infrared emitter diode (IRED). They depend directly on the radiant intensity of the emitter, set by the IRED bias current. As is known, this current presents a drift with temperature, which will be transferred to the distance estimation method. This paper proposes an alternative approach to remove temperature drift in the distance estimation method by eliminating the dependence on radiant intensity. The main aim was to use the relative accumulated energy together with other defined models, such as the zeroth-frequency component of the FFT of the IRED image and the standard deviation of pixel gray level intensities in the region of interest containing the IRED image. By using the abovementioned models, an expression free of IRED radiant intensity was obtained. Furthermore, the final model permitted simultaneous estimation of the distance between the IRED and the camera and the IRED orientation angle. The alternative presented in this paper gave a 3% maximum relative error over a range of distances up to 3 m.