1 / 13

Abílio Azenha and Adriano Carvalho

5th IFAC International Symposium on Intelligent Components and Instruments for Control Applications, Aveiro, 9-11 July 2003, Portugal. Instrumentation and Localisation in Quasi-Structured Environments for AGV Positioning. Abílio Azenha and Adriano Carvalho

july
Download Presentation

Abílio Azenha and Adriano Carvalho

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. 5th IFAC International Symposium on Intelligent Components and Instruments for Control Applications, Aveiro, 9-11 July 2003, Portugal Instrumentation and Localisation in Quasi-Structured Environments for AGV Positioning • Abílio Azenha and Adriano Carvalho • Institute of Systems and Robotics, Faculty of Engineering, University of Porto, • Rua Dr. Roberto Frias s/n, 4200 - 465 Porto, Portugal • E-mail: azenha@fe.up.pt, asc@fe.up.pt

  2. Abstract: This communication addresses the automated guided vehicles (AGVs) positioning issue. A summarised state-of-the-art section is included and the dead-reckoning algorithm is analysed with a support on a triangulation scheme. This scheme is based on ultrasonic sensors or electromagnetic wave transmitter/receiver antennas sets. Simulation results for AGV movement to validate the control system efficiency and implementation issues of work in progress are presented.

  3. Overview Section 2 sketches a state-of-the-art overview summary. Section 3 derives from WMRs technological knowledge to a model for AGV positioning in quasi-structured indoors environments and deals with the dead-reckoning algorithm and triangulation method. Section 4 outlines the controller design and simulation results. Section 5 introduces the current implementation issues. Section 6 draws the main conclusions and future research work issues.

  4. STATE-OF-THE-ART • The development of a positioning system is based on the system measurement requirements. Typically, different classes of requirements according to either the vehicle and/or its movement can be found. • global navigation, with ability to determine the object position in absolute or map-referenced terms, and to move to a desired destination point; • local navigation, with ability to determine the object position relative to objects (stationary or moving) in the environment, and to interact with them correctly; • personal navigation, which involves being aware of the positioning of the various parts that make up oneself, in relation to each other and in handling objects.

  5. STATE-OF-THE-ART Automatic warehouse example with AGVs

  6. STATE-OF-THE-ART • Dead-reckoning • Odometry • Global Positioning Systems (GPS) • Inertial Navigation Systems (INS) • ‘Pseudo-satellites’ (pseudolites) • Building Positioning System (BPS) • Ultrasonic (or sonar) and laser (or lidar) sensor triangulation • RF based triangulation algorithms

  7. DEAD-RECKONING ALGORITHM AND TRIANGULATION METHOD Figure 1. Adopted WMR model.

  8. DEAD-RECKONING ALGORITHM AND TRIANGULATION METHOD where (x1, x2, f) is the current WMR pose and (x10, x20, f0) is the previous time step WMR pose. The triangulation method updates the AGV position from time to time and an internal AGV compass updates its orientation. The triangulation sensors analysed are ultrasonic and laser/RF beams, based on distances and angles calculation triangulation algorithm

  9. DESIGN AND SIMULATION Figure 3. AGV control scheme. The control system attempts to align f with ft. In this study the control scheme is implemented by the AGV micro-controller in a way as depicted in Figure 3. Figure 2. AGV orientations model.

  10. DESIGN AND SIMULATION a) Figure 4. The AGV reference trajectory. b) Numerical Values: R = 0.05 m, b= 0.2 m, l = 0.4 m, tw = 0.01 m, mc = 10 Kg, mw = 0.45 Kg, Fvi = 0.5 Nms, Kti = 31.1 mNm/A, KIi = 0.03 A/V and ri = 66, i = 1, 2 Figure 5. a) AGV trajectory response; b) AGV position error signals.

  11. IMPLEMENTATION ISSUES Work in progress: • localisation based on the 2.4 GHz band (ISM) • chosen core micro-controller is the Atmel AT90S8535 • AVR-GCC freeware C compiler was adopted to develop the program • optical encoders are Hewlett-Packard HEDS-5540-A06 with a 500 points per revolution resolution • PWM dc motors control bridges adopted are two Allegro Microsystems integrated circuits A3952SB (one for each dc motor)

  12. IMPLEMENTATION ISSUES Work in progress: • 2.4 GHz transmitter based on a VCO (MAX2750) • VCO output power is about ‑3 dBm and if rising that value is wanted a PA such as MAX2240 should be adopted • RSSI circuit based on AD8361 rms (root-mean-squared) converter • AD8361 response is nearly linear to the input power and the output is a quasi (slow varying) dc voltage. The absolute maximum input power is 10 dBm at a matched antenna impedance of 50 W

  13. CONCLUSIONS AND FUTURE WORK • At present, a small WMR for position measurement and control purposes is being built. Its electromechanical structure is already implemented • The trajectory is a priori known so the path planning is made off-line, because the AGV will be placed in quasi-structured and flexible layout indoors environments • Triangulation algorithms with electronic beacons scattered strategically around the quasi-structured indoors workspace are planned to be used. It is expected that a scanning triangulation frequency less than 1 Hz is sufficient for each moving AGV in the environment, due to its low speed

More Related