Robot’s Navigation System
Student: Dinh Viet Thang
•CONTENT
•I. Introduction
•II. Navigation system
•III. Hardware
•IV. Control diagram
•V. Conclusions
I. Introduction
- Discussion presents a simple method to control robot
- System is included two main modules:
+ Image-processing module to identify objects by
TRDB-D5M Sensor and FPGA DE2-70
+ Module determines the distance the object using
PIC 18F4550 processor and ultrasonic sensors
SFR05
•II. Introduction about navigation system
•- To support decision of robots, you need a navigation system.
- This system includes the horizontal processing and distance processing.
- The horizontal navigation is executed by image processing module.
- The advantage of horizontal position (relative to object): robot can
move in any environment without the need to have the navigation bar.
•- This helps shorten the way, energy savings and greater flexibility in
handling.
•- Navigation system with distance is treated by the radio transceiver
module or ultrasound.
- Image processing technology and identification technology is complicated.
- Images are obtained from the camera is always disturbed.
- The noise reduction processing and target identification becomes difficult
and resource consuming.
- So image processing technologies with robotic devices that require low
profile should have the support of other technologies such as ultrasound,
infrared, ... to improve the accuracy and speed .
III. Image processing and Ultra-Sonic Ranger sensor
1. Image-processing module to identify objects
2. SRF05 sensor module to calculate the distance
1. Image processing module
•The block diagram
•
*Identify the color:
- The color is stored in image files by: each pixel will be three
consecutive bytes, each byte is a color of the Red, Blue, Green.
• Synthetic colors that will make the color of the pixel. - Each
separate color% rate is fixed colors with brightness. (Eg white (R,
B, G) = (1:1:1))
- Read image file to get values (R, B, G), compute the % of each
pixel
•- Compare with standard color, and check the brightness of it,
with the range is allowed or not.
• (we can sets standard color suit your purposes).
•Function blocks
•* TRDB_D5M
•- 5 Mega Pixel from TERASIC (2592 by 1944 pixel) color CMOS Camera.
•- Its had on board 12bits ADC
•- The maximum pixel clock according to the specifications is 96MHz
•Parameter of D5M Camera
•- I2C_CCD_Config
•I2C is a two line serial bus. This bus is mainly used for communicating low bandwith signals such as control
signals between different integrated circuits on board.
•- VGA_Controller
•The VGA_Controller generates the pixel addresses on the display and the hsync and vsync signals.
•- SdRam_Control_4Port
•- Nios-II processor
•The Nios-II processor architecture has been made in SOPC and its instance is called DE2_70_SOPC. It uses the
on board 2MByte SSRAM for program code and data, it interfaces with the 4 port memory controller. In this way
the NIOS-II processor can access the frame buffer and communicate via the JTAG UART with the host PC or
micro chip (PIC 18F4550)
•*All blocks are created on the FPGA
Illustrates
•- When hovering over the picture with the mouse, the lower left small window will show a blown up
picture, together with the coordinates of the center pixel and the RGB values.
•- Also shown is a histogram for the 3 colors and the size of the picture.
2. SRF05 - Ultra-Sonic Ranger
-Ultra-sonic sensor SRF05 capable of detecting obstacles with the range 1 cm-> 4 m
- Pin diagram to connect
•Operating of SFR05
-SRF05 need a high level pulse, width > = 10uS on Triger Pin.
- After receiving a pulse from the Triger pin
- SRF05 will create 8 pulse to generate ultrasonic pulses
- Make echo pin to high level pulse
- The width of high level pulse on Echo pin corresponding with distance of the obstacles
to srf05
- If no obstructions, Echo Pin will be returned to low level after 30ms
III. Control method
•SRF 05
•Image processing
•Module
switches
•Micro Chip
•PIC 18F4550
•Load
•III.1 Identify control object
•Image
•Camera
•TRDB-DB5
•Micro Chip
•PIC 18F4550
•FPGA
•Data width
•12 Bit
•RS232
•Image processing by FPGA and Camera
- The objective of this module is to identify objects (defined colors)
- Calculate eccentricity of the robot is compared to the object horizontally.
- The processing of this module in the diagram.
•Picture from
•camera
•Changed to RGB color
•system
•identify control object
•(already know the color )
•Calculate
• eccentricity position
•(X: Horizontally)
Transmit to PIC
Calculate the distance of object to Robot
•object
ultrasonic sensor
SRF05
Micro chip
PIC 18F4550
•Begin
•- Detector object
•- Read Distance
•Y
•Right
•Deviance
•Check condition
•Distance = 80cm
•N
•Check condition
•Distance = 10cm
•Y
•Check condition
Left
Deviance
• deviance ?
•End
Processing Left
Deviance
Processing Right
Deviance
Rotated to find the object
Not Found?
•N
IV. Conclusions
•- When using the camera and SFR05 sensor, works well in both
environment : indoor and outdoor .
•- With more noise (influenced by temperature or light…), less
accurate and the same with larger objects .
- Self image processing technology has certain disadvantages,
but when combined with other technologies to improve
efficiency significantly.
References
[1]. Tài liệu về DSP Development Kit, Stratix Edition ở Website:
http://www.altera.com/products/devkits/altera/kit-dsp-2S60.html.
• [2]. Trần Ngọc Phụng, Trần Thị Điểm, Cao Trần Bảo Thương,
Huỳnh Hữu Thuận, Thực Hiện Một Số Thuật Toán Dò Tìm
Chuyển Động Trên FPGA
[3] Nigel Gardner (2002), An introduction to programming The
Microchip PIC in CCS C, Bluebird Electronics, USA.
[4] TRD5M – 5 Mega pixel digital Camera Development kit 2008
Terasic