Geintra

Departamento de electronica Universidad de Alcala

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    Demos

    In this page you'll find several demonstrations of the GEINTRA available technology.

    Media coverage:

    Mobile robot localization with Multiple Ultrasonic LPSs and odometry

    This video shows the operation of a Local Positioning System for Wide areas using Ultrasounds (U-WLPS). For the localization of a mobile robot both its onboard ondometry system and six single ultrasonic localization subsystems U-LPS are used. The positions obtained using the U-LPS (when available) are used to correct the odometry. The positions obtained by both positioning systems are merged using a H-infinite filter.

    In the video:

    • Top left is the actual movement of the mobile robot. It is speeded up by a factor x2 in the video to the left, and at normal speed in the video to the right.
    • The rest of the image is the plan of the floor and the trajectory followed by the robot (with a zoom in the top right side). With:
      • the blue dots are the beacons' projections of the US-LPSs (five beacons each).
      • the green dots are the positions obtained with the LPS (when available).
      • the red trajectory is the one obtained using only the odometry system.
      • the black trajectory is the one obtained after combining positions from the LPS and odometry systems using the H-inf filter. It can be seen that through the filter H-infinity the robot is able to recover from cumulative errors caused by odometry outside the coverage areas of each single LPS. Furthermore, this filter smoothes erroneous measurements from ultrasound systems.

    Ultrasonic LPS using Generalized Cross-Correlation

    This video shows the performance of an ultrasonic LPS system composed of five beacons on the ceiling that emit synchronoulsy. Each one of the beacons has assigned a 1023-Kasami code that modulates a carrier signal of about 40kHz. The receiver, on the mobile, performs a discriminatation of the signals coming from the different beacons by correlation, calculates the Time Difference of Arrivals and performs the positioning using trilateration. In the video:

    • The mobile follows a constrained circular trajectory, as ground truth.
    • Different reflectors provoke multipaht (the worst situation for a US-LPS system).
    • In the last part of the video a drill machine is turned on introducing a big amount of acoustic noise.
    • To see:
      • Top left: real movement, on the screen of the computer the actual signal captured by the receiver.
      • Top center: calculated positions, in black using standard cross-correlation (CC) and in red using GCC.
      • Top right: A zoom of the top-center image.
      • The bottom part of the video is composed of ten figures: the upper part of them correspond to the CC for each one of the beacons and the lower part correspond to the GCC.



    Intelligent guiding of wheel chairs

    • Advanced Guiding of Wheel Chair (2005): This sequence shows the behaviour of a non-contact Head Controller over an advanced wheelchair (SIAMO prototype). Using only head movements this user is able to go into a standard elevator; this is done without pressing or moving any kind of physical device. The key of the system is a patented IR detector that locates user's head an evaluates its movements according to a predefined set of commands. This work was made in 2005, in the Electronics Department of the University of Alcala (Spain, www.geintra-uah.org); the IR detection algorithm was designed by Mr. Henrik Vie Christensen (who drives the chair) from the Dept. of Control Engineering, of the Aalborg University (Denmark).

       

       

    • SIAMO Intelligent Wheelchair (1996-1999): This video shows a short resume of SIAMO project (SIAMO = Integral System for Assisted Mobility). Audio track is in Spanish. This project was under development between 1996 and 1999 in the Electronics Dpt. of the University of Alcala (Spain, www.depeca.uah.es). Main focus was to study, design and test several Human Machine Interfaces over an advanced wheelchair platform, also designed by the same research group. More information in: www.geintra-uah.org/en

       

       

    • UMIDAM Intelligent Wheelchair (1991-1994): This video shows a short resume of an Intelligent Wheelchair called UMIDAM (UMIDAM = Intelligent Mobile Unit of Assisted Mobility). Audio track is in Spanish. This project was under development between 1991 and 1994 in the Electronics Dpt. of the University of Alcala (Spain, www.depeca.uah.es). A first prototype, controled by vocal commands, was shown inside the ONCE stand in the EXPO'92 of Sevilla (Spain). More information in: www.geintra-uah.org/en

       

       

    Ultrasound Indoor Location System

    • Ultrasound Indoor Location System (2009): This sequence shows the behaviour of an experimental ILS (Indoor Location System) based on codified Ultra Sound beacons. This research have been made in the GEINTRA labs of the University of Alcala (Spain) in 2009; web-page: http://www.geintra-uah.org/en. In this video, ILS uses LS (Loosely Synchronized) codes to measure accurately the TOF (Time Of Flight) between the target and a set of reference beacons. To demonstrate system behaviour a mobile robot moves inside the ILS coverage area; while moving, two different set of data can be seen on screen: conventional odometry is shown with a green line; ILS positioning is shown unfiltered (red line) and filtered (black line). Around second six, the robot is taken up while running: odometry estimation show a growing error as expected, while ILS estimation remains low and keep track of moving object in any time.

       

       

    Intelligent Transportation System for Cooperative Guidance of Electrical Vehicles in Special Scenarios (COVE project 2010)

    This research project deals with the design and implementation of an electronic architecture (sensorial, control and communication) that contributes to the cooperative guidance of transport units: platoon formed by electrical vehicle prototypes.

    The following results have been achieved: Development and implementation of control solutions so that the followers units can automatically perform a stable leader-following process in non-linear trajectories. Design and implementation of algorithms which deal with merge and split manoeuvres of units related to a convoy. Design of an intelligent system for attendance to the leader in the decision making process on the optimal and efficient route, according to previous experiences.

    The following videos show several experimental tests carried out in the laboratories of the Polytechnic School at the University of Alcala, using P3-DX robotic units as electrical vehicle prototypes. The convoy departs from one laboratory, moves along a corridor and arrives to the adjoining laboratory (video sequence 1) or to the original one (video sequence 2).

    Robot Routing Considering Uncertainties in Travelling Times (2011)

    This section shows two demonstrations of robot routing in a real simplified transport scenario, showed in the following figure.

    There are two Pioneer P3-DX units, one of them working as a convoy leader continuously moving around the periphery, and another identical robot working as a pursuer which challenge is to merge the convoy in the optimal meeting point (minimum merging time).

    The scenario includes different areas with different statistical values (mean and variance) of velocities (see figure), this way a random velocity is dynamically assigned to each robot once a new node is reached. In order to delimit the randomness inherent to the problem, the parameter “risk factor” is considered, limiting the probability of the convoy reaching the merging node before the pursuer (failed merging maneuver).

    • The first video was taken in the most conservative condition (0% risk factor). The meeting point is decided in order to reduce the probability of failure, but the waiting time is notably large (direct link to mpg video (61MB), in case you have problems with flash)

       

       

    • The second video was taken in the less conservative condition (100% risk factor). In this case, the required time for the meeting maneuver has been considerably reduced. However the number of re-planning for the pursuer unit has increased as well as the number of the percentage of failed tests (direct link to mpg video (92MB), in case you have problems with flash)

       

       

    Self-triggered control of a remotely operated P3-DX robot (2013)

    This video shows an example of self-triggered application to the remote control of a robotic unit. Figure 1 displays the trajectory followed by the robot which is controlled by a PC through a wifi link. The classical sampled digital control is replaced by a self-triggered solution according to scheme control of Figure 2. (you can also get the full quality wmv file (66Mb))

    Figure 1 Video

    Figure 2

    Remote adaptive self-triggered control for trajectory tracking of two P3-DX robots (2013)

    The video shows the trajectory tracking of two robotic units simultaneously controlled by a remote centre through wireless link (WLAN IEEE 802.11g). An adaptive self-triggered control solution has been implemented considering the effect of time-varying network delays, only the information provided by the odometric system is feedbacked for trajectory tracking. On the left-hand side the trajectory followed by the robots at the laboratory area is included. On the right-hand side the tracking error and the inter-sampling time is dynamically plotted. This research work has been made in the GEINTRA labs of the University of
    Alcala (Spain) in 2013 (you can also get the full quality mp4 file (63Mb)).

    Human-machine interfaces based on video processing

    • Virtual mouse based on face tracking techniques (2010): The video shows a very simple HMI (Human-Machine Interface) based in AAMs (Active Appearance Models). The user is able both to move a cursor around the screen only with head movements, and simulate a mouse left click opening the mouth (you can also get the full quality avi file).

       

       

    Acoustic based audio localization systems

    • SRP-PHAT based acoustic localization system: The green sphere represents ground truth
      speaker position, and the red one is the system location
      estimation. No tracking is attempted, just plain memoryless
      localization. The SRP-PHAT power grid is partially shown, with the
      cube intensity being related to the the received signal power in the
      corresponding grid location (you can also get the full quality video file).

       

       

    • Microphone arrays modeled as perspective cameras (3D map, short footage): Acoustic 3D map estimated from a single microphone array modelled as a
      perspective camera. x and y axes represent angle variations in azimuth
      and elevation, respectively, with the array center being the local
      coordinate center. The z axe represents acoustic power coming from the
      corresponding direction in 3D space (azimuth, elevation). The
      microphone array is composed by 4 elements, three of them linearly
      aligned and the third one orthogonal to the others (inverted
      T-shape). The speaker is slightly moving during the sequence (you can also get the full quality video file).

       

       

    • Microphone arrays modeled as perspective cameras (2D map, long footage): Acoustic 2D map generated from the 3D surface estimation described
      above. In this case, ground truth is also shown as a red circle (the
      ground truth being the circle center). x and y axes represent angle
      variations in azimuth and elevation, respectively, with the array
      center being the local coordinate center. The speaker is slightly
      moving during the sequence (you can also get the full quality video file).

       

       

    • Microphone arrays modeled as perspective cameras (2D map): Acoustic 2D map generated by a linear microphone array composed of four equispaced microphones
      (so that only azimuth can be identified. x and y axes represent angle
      variations in azimuth and elevation, respectively, with the array
      center being the local coordinate center. The speaker was static
      during all the sequence (you can also get the full quality video file).

       

       

    • Sector based acoustic localization using multiple arrays: Demonstration of sector based localization, using two circular
      arrays. The system identifies the active sectors for each array and
      run a SRP-PHAT algorithm in the intersection to determine the speaker
      position. The black circle is the ground truth position, and the red
      one is the estimated location. The active intersections are highligted
      also in red (you can also get the full quality video file).

       

       

    Video based localization and tracking systems

    Video based full body tracking systems

    Media coverage