Team chopper subterranean mapping performed by co operative helicopters
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Team Chopper Subterranean Mapping performed by co-operative helicopters. Shirley Choi Bejan Hafezzadeh Joseph Kaiser Sean Norwood Itay Tenne. Introduction. Subterranean Mapping Autonomous Co-operative Helicopters Avionics System Can Avionics Interface Board (CAIN). Interface Board.

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Team Chopper Subterranean Mapping performed by co-operative helicopters

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Team chopper subterranean mapping performed by co operative helicopters

Team ChopperSubterranean Mapping performed by co-operativehelicopters

Shirley Choi

Bejan Hafezzadeh

Joseph Kaiser

Sean Norwood

Itay Tenne


Introduction

Introduction

  • Subterranean Mapping

  • Autonomous Co-operative Helicopters

  • Avionics System

  • Can Avionics Interface Board (CAIN)


System overview

Interface

Board

Interface

Board

Interface

Board

Interface

Board

Interface

Board

Interface

Board

Flight

Computer

System Overview

Satellites

INS

Pressure Sensors

IMU

GPS

Magnetometer

RS232

RS644

RS232

RS232

RS232

Power Generator

CAN Multi-Drop Bus

Power Board

All Boards

Interface

Board

Interface

Board

Servo Isolation

Servo battery

RS232

PWM signals

On board Radio

Servos

RC receiver

For test

and debug

RS232

Ground Radio

RC Transmitter

Host PC

for COM and

configuration

USB

Error Correcting GPS

Multi-Drop Bus

To GPS


Helicopter s on board devices

Helicopter’s On-board Devices

  • CAIN Boards

  • 586-Engine-P (Flight computer)

  • Servos

  • IMU

  • RC receiver

  • GPS


Cain board

CAIN BOARD

  • Chopper Avionic Interface Node

  • Interfaces between the CAN bus and the individual devices.

  • Built around an Atmel Processor

  • Contains UARTs(RS-232), PWM generators, Digital Output and Inputs

  • Individually programmable


Cain board block layout

CAIN Board Block Layout

TWI/SPI

ADC

addr

ISP

JTAG

Addr/data

RS232

CAN transceiver

/

CAN bus

NV RAM

RS232

Atmel

AT90CAN128

RS644

LEDs

EEPPOM

PWM

(6 channels)

Jumpers/Selectors


586 engine p

586-Engine-P

  • Main processing unit for the helicopter

  • Based around an AMD 586 processor

  • On board CF memory card reader

  • Will read the sensor inputs from on-board devices and RC controller and send corrected signals to the servos

  • Will include the control law to perform the augmented control on the helicopter


Servo

Servo

  • A servo is used to mechanically control the helicopter

  • It is controlled by PWM signals produced by error-corrected signals from the remote-controller unit


Team chopper subterranean mapping performed by co operative helicopters

IMU

  • An Inertial Measurement Unit gives 6 key measurements of the helicopter

  • These measurements are sent to the flight computer via the CAN bus

  • The flight computer processes this information for error correction


Rc receiver

RC receiver

  • A remote controller (RC) is used to control the orientation of the helicopter

  • The RC receiver receives human input signal

  • Signal decoded through CAIN board

    • Sent to servos for full manual control

    • Or, dispatched on CAN bus to be processed by augmented control system


Team chopper subterranean mapping performed by co operative helicopters

GPS

  • GPS unit on helicopter provides flight computer with latitude, longitude, and altitude measurements

  • The GPS used for fully autonomous flight


Risk analysis

Risk Analysis

  • Power consumption on board

  • Control loop (simulation)

  • Noise

    • EMI, Cross-Talk, ESD

  • Physical vibration

  • Time delay (transmission)


Contingency plan

Contingency Plan

  • Shopping cart

  • Powered by batteries

  • No control loop (manually driven)

  • PCBs spaced out – less noise

  • Minimized physical vibration


Part list

Part List

Provided by Prof. Meyer:

Total: $2373


Schedule

Schedule


Future development

Future Development

  • CAIN is versatile, it is capable of interfacing with unknown devices.

  • More modules

    • Pressure sensor

    • Magnetometer … etc

  • pre-filtering data on CAIN

  • Development of the multi-master model

  • Implement advance control system

  • Path finding ability


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