ATOPET AUTOMATIONS: Embedded Systems and Robotics Training

… Conceptual idea turns innovative realities …

Aniebiet M. Ezekiel

(MIET, MAUVSI, MNSE, MIEEE, MNIEEE)

Executive Director

Office Line: (+234)0909-400-9029         eamicheal@atopetautomations.com

www.atopetautomations.com

Services:

• Teaching and Consultancy:  Automation, Embedded Systems, Robotics & Mechatronics
• Innovative research, design, implementation and fabrication in automation
• Hand – on – Experiences: Electrical/Electronic hardware and software
• Project Design, implementation and commissioning
• Theoretical and Practical training
• Control and instrumentation
• Career Counseling
• Research and Reporting
• Individual Coaching, Tutoring
• Continuous Professional Development (CPD)
• Research Laboratory/Demonstration and Exhibition
• Electrical Electronic component Sales, imports and exports

 … Bridging the gap between theory and the real world….

Affiliates: ARM Mbed, National Instruments, University of Derby, University of Port Harcourt, Institute of Control and Measurements

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Training Details:

The Embedded System and Robotic Training combines two main concept; application of measurement and control principles within the context of embedded systems in an interesting way. While a study of both hardware and software on ARM cortex M3 controller platform is involved, there is perhaps an emphasis on software techniques.

This training assumes that you may have little to no prior knowledge of embedded systems or microprocessors, as well as programming experience. However, if you have, ooopps quite great, if you haven’t, you should be put through in the course of the training, but you will need to do some background work

TRAINING INFO

Training Learning Outcomes

On successful completion of the module, students will be able to: 1.     Understand basic electronics, identify any electronics and familiarize with electronic tests and measurement units/facilities 2.     Identify robot, innovate and develop self-activity robots 3.     Design automation systems and build prototypes Embedded C Programming on modern embedded systems platform 4.     Design and commission the hardware of a microcontroller-based system, including interface to sensors and actuators

The training which last for 48 hours will be completed withing a month. The next batch of training resumes every month end.

On completion of the project you should have Designed an Implementated a Practical mobile robot. Click to see

ROBOT

Autonomous Guided Vehicles

Overview

In realistic situations, planets, space and hazardous areas are dynamic, uncertain and unpredictable. These unpredictable circumstances like adverse weather, exposure to radiation and toxic wastes etc. limit human’s capacity to carry out safe research and exploration activities. This project focuses on providing a novel solution to safe research and exploration in these environs through autonomous vehicle technology.

The sophistication of a modern and high-end vehicle requires more Electronic Control Units (ECUs) interfaced with sensors and actuators to interact with the physical world. In this project, an Autonomous Guided Vehicle (AGV) whose multiple ECUs were networked using Controller Area Network (CAN) protocol, a more robust and reliable in-vehicle communication protocol was built. The main contribution of this study is the development and implementation of a fully AGV with a reliable communication protocol and a surveillance unit to withstand unforeseen circumstances in a dynamic environment.

This work also provides an additional research tool to safe operation of automated vehicles in uncertain environmental conditions. It also makes useful contributions to wireless ignition and autonomous path navigation for critical-safety systems in the automotive industry. Findings from this project will stimulate further research into AGV technology and possibly the development of more reliable automotive protocols.

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DEMO

Summary

This project sought to overcome the challenge posed by the Free Ranging On Grid (FROG) vehicles by building an unguided vehicle. Autonomous vehicles are the most suitable for carrying out tasks in dynamic, unstructured and risky environments, eliminating the hazards humans are exposed to. Most available AGV are low autonomy systems which require some driver interaction. This challenge was overcome by the fully AGV developed in this project and therefore, did not require any map as a guide. Thus, the sensors and intelligent devices used in this vehicle are steps toward developing a fully autonomous vehicle. A competent processor, such as the Mbed, that could perform professional rapid prototyping was used to carry out the complex intelligent tasks and the emergent coordinated activities of the vehicle.

The distributed control structure was implemented with multiple Mbed processors networked to achieve an integrated solution of the vehicle’s complex tasks. Communications between the six distributed ECUs were realized on a CAN network. CAN is a highly reliable automotive protocol used in safety-critical systems over a two-wire bus line and has a maximum bit rate of 1Mbit/s. The CAN bus reliability and fault tolerance features of this vehicle were analysed by injecting faults into the vehicle ECUs. Being a robust network, faulty node(s) disconnected from the bus, while others maintain reliable communication.

The entire vehicle was powered by a 12 [V] rechargeable lead acid battery which was regulated to 5 [V] required by each subsystem. Software with an interactive GUI was created for the wireless start/stop controller called BlueIgnition. The BlueIgnition controller was developed using a ToothPick transceiver which has an inbuilt PIC microcontroller integrated with a LinkMatik Bluetooth module. The controller was used to start or stop the vehicle from a Windows PC via Bluetooth.

When the vehicle was started, it detected and manoeuvred from any object that obstructed its exploration of the environment. It also surveyed the environment using an on-board camera which captured images of the obstructed areas and notified intrusion alerts on the remote PC. The vehicle had the capability of acquiring and logging the temperature, humidity and dew point of the explored environment onto the PC using the Tera Term. The temperature condition of the environment was used to control the vehicle’s speed. The vehicle’s activities were diagnosed and communicated to the PC. When the exploration was completed, the vehicle was remotely stopped and the captured images stored on the Mbed flash memory were imported to a PC.

Finally, after some hardware debugging and software restructuring, a fully autonomous explorer vehicle was achieved with a wireless ignition system that presents a better solution to the mechanical and remote control ignition challenges faced in the automotive industry. A similar method was applied by Shaw and Politano in 2008 to control home devices; however, this work creates a new automotive solution as there was little to no literature indicting this application in vehicles.

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YouTube Demo