Embedded Control for Mobile Robotic Applications E-Book

Leena Vachhani

• Herausgeber: John Wiley & Sons
• Kategorie: Wissenschaft und neue Technologien
• Serie: Wiley-IEEE Press Book Series on Control Systems Theory and Applications
• Sprache: Englisch

Seitenzahl: 226

Veröffentlichungsjahr: 2022

Beschreibung

An all-in-one resource for designing and implementing embedded control in mobile robotics In Embedded Control for Mobile Robotic Applications, a distinguished trio of researchers delivers an authoritative and fulsome resource for understanding embedded control and robotics. The book includes coverage of a variety of embedded platforms, their use in controller implementation, stability analyses of designed controllers, and two new approaches for designing embedded controllers. The authors offer a full chapter on Field-Programmable-Gate-Array (FPGA) architecture development for controller design that is perfect for both practitioners and students taking robotics courses and provide a companion website that includes MATLAB codes for simulation and embedded platform-specific code for mobile robotic applications (in Embedded C and Verilog). The two approaches discussed by the authors--the top-down methodology and the bottom-up methodology--are of immediate practical utility to both practicing professionals in the field and students studying control applications and mobile robotics. The book also offers: * A thorough introduction to embedded control, including processor, IC, and design technology, as well as a discussion of limitations in embedded control design * Comprehensive explorations of the bottom-up and top-down methods, including computations using CORDIC, interval arithmetic, sliding surface design, and switched nonlinear systems * Practical discussions of generic FPGA architecture design, including Verilog, PID controllers, DC motors and Encoder, and a systematic approach for designing architecture using FSMD * In-depth examinations of discrete-time controller design, including the approximation to discrete-time transfer function and embedded implementation stability Perfect for practitioners working in embedded control design and control applications in robotics, Embedded Control for Mobile Robotic Applications will also earn a place in the libraries of academicians, researchers, senior undergraduate students, and graduate students in these fields.

Leseprobe

Table of Contents

Cover

Title Page

Copyright

Preface

Acknowledgments

Acronyms

Introduction

About the Companion Website

1 Embedded Technology for Mobile Robotics

1.1 Embedded Control System

1.2 Mobile Robotics

1.3 Embedded Technology

1.4 Commercially Available Embedded Processors

1.5 Notes and Further Readings

2 Discrete-time Controller Design

2.1 Transfer Function for Equivalent Discrete-time System

2.2 Discrete-time PID Controller Design

2.3 Stability in Embedded Implementation

2.4 Notes and Further Readings

3 Embedded Control and Robotics

3.1 Transformations

3.2 Collision Detection and Avoidance

3.3 Localization

3.4 Path Planning

3.5 Multi-agent Scenarios

3.6 Notes and Further Readings

4 Bottom-up Method

4.1 Computations Using CORDIC

4.2 Interval Arithmetic

4.3 Collision Detection Using Interval Technique

4.4 Free Interval Computation for Collision Avoidance

4.5 Notes for Further Reading

Notes

5 Top-Down Method

5.1 Robust Controller Design

5.2 Switched Nonlinear System

5.3 Notes and Further Readings

6 Generic FPGA Architecture Design

6.1 FPGA Basics and Verilog

6.2 Systematic Approach for Designing Architecture Using FSM

6.3 FPGA Implementation

6.4 Parallel Implementation of Multiple Controllers

6.5 Notes and Further Readings

Note

7 Summary

Bibliography

Index

End User License Agreement

List of Tables

Chapter 4

Table 4.1 Truth table for

Table 4.2 Interval notations for sub-intervals

Chapter 6

Table 6.1 Truth table for PID control logic

Table 6.2 Truth table for sliding-mode control logic

Table 6.3 FPGA area consumption for PID controller with 32-bit input

List of Illustrations

Chapter 1

Figure 1.1 Block diagram of an embedded control system

Figure 1.2 A point moving in planar environment

Figure 1.3 Generic 2D robot model

Figure 1.4 Differential drive mobile robot schematic illustrating wheel arra...

Figure 1.5 DDMR rotation when wheel velocities are same but in opposite dire...

Figure 1.6 Circular motion of the DDMR

Figure 1.7 Illustration for deriving kinematic model of DDMR

Figure 1.8 Schematics for front wheel steering with various wheel arrangemen...

Figure 1.9 Illustrations for working principle of FWSR

Figure 1.10 Geometric interpretation of different discretization methods

Figure 1.11 Typical 3D position representations

Figure 1.12 Illustration of 3D orientations

Figure 1.13 Schematic of a quadcopter

Figure 1.14 Schematic of six-thrusters configuration;

show typical placeme...

Figure 1.15 Various layers of IC technology

Figure 1.16 Block diagram of a typical microcontroller

Figure 1.17 Typical architecture layout of an FPGA; LUT stands for look-up t...

Chapter 2

Figure 2.1 Block diagram of an embedded control system

Figure 2.2 Illustration of trapezoidal integration

Figure 2.3 Exact discrete-time model of a continuous-time system

Figure 2.4 Nature of frequency amplitude response of ZoH

Figure 2.5 An open-loop control system with quantizer

Figure 2.6 A closed-loop system with quantizer

Chapter 3

Figure 3.1 Autonomous robot planning as a control system

Figure 3.2 Rotation in 2D

Figure 3.3 Rotation in 3D

Figure 3.4 Vector field histogram

Figure 3.5 Illustration of curvature velocity technique

Figure 3.6 Illustration of potential function technique

Figure 3.7 Improvement in potential field technique illustrating the closest...

Figure 3.8 Connectivity graph

Figure 3.9 Illustration of cost computation of each cell using Dijkastra's a...

Figure 3.10 Illustration (continued) of cost computation of each cell using ...

Figure 3.11 An illustration of iterations in the A* algorithm

Figure 3.12 RRT algorithm

Figure 3.13 Inter-agent collision detection

Chapter 4

Figure 4.1 Architecture of conventional CORDIC.

Figure 4.2 Interval intersection and interval hull

Figure 4.3 Inclusion function (Jaulin et al., 2001)

Figure 4.4 Colliding objects: the decision-making robot and dynamic obstacle...

Figure 4.5 Interval representation of velocities of decision-making robot th...

Figure 4.6 An illustration of iterations of bisection with respect to

Figure 4.7 An illustration of iterations of bisection with respect to

Figure 4.8 Collision-free interval

Chapter 5

Figure 5.1 Stabilization of a single integrator using state feedback

Figure 5.2 Effect of state feedback control on a single integrator with dist...

Figure 5.3 Stabilization of a single integrator using discontinuous input

Figure 5.4 Stabilization of a single integrator affected by disturbance (

),...

Figure 5.5 Stabilization of a double integrator by a sliding-mode controller...

Figure 5.6 Double integrator states trajectory under the influence of slidin...

Figure 5.7 Engagement geometry between current position of the robot and the...

Figure 5.8 Trajectory taken by a unicycle vehicle in 2D using proposed contr...

Figure 5.9 3D Dubin's vehicle kinematics in an inertial frame

Figure 5.10 Illustration of the sliding surfaces on engagement geometry

Figure 5.11 Trajectory taken by a unicycle robot in 3D using proposed contro...

Figure 5.12 Block diagram of embedded sliding-mode controller for 3D positio...

Figure 5.13 Stability condition on multiple Lyapunov functions

Figure 5.14 Stability condition on multiple Lyapunov functions when the valu...

Figure 5.15 Engaged subsystem: the

th robot is shown closest to the

th rob...

Figure 5.16 Block diagram of embedded controller for swarm aggregation appli...

Chapter 6

Figure 6.1 Illustration of combinational and sequential circuits

Figure 6.2 Concept of using submodules

Figure 6.3 An illustration of 4-state FSM

Figure 6.4 Finite state machine (FSM) as a black box

Figure 6.5 Flow chart for PID controller

Figure 6.6 Architecture for PID controller

Figure 6.7 State machine for PID controller

Figure 6.8 Control logic for PID controller

Figure 6.9 Flow chart for sliding-mode controller

Figure 6.10 Architecture for sliding-mode controller

Figure 6.11 State Machine for sliding-mode controller

Figure 6.12 Control logic design for sliding-mode controller.

Figure 6.13 Block diagram illustrating topmost Verilog module

Figure 6.14 Parallel control loops using FPGA

Guide

Cover

Table of Contents

Title Page

Copyright

Preface

Acknowledgments

Acronyms

Introduction

About the Companion Website

Begin Reading

Bibliography

Index

End User License Agreement

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IEEE Press445 Hoes LanePiscataway, NJ 08854

IEEE Press Editorial BoardSarah Spurgeon, Editor in Chief

Jón Atli Benediktsson

Andreas Molisch

Diomidis Spinellis

Anjan Bose

Saeid Nahavandi

Ahmet Murat Tekalp

Adam Drobot

Jeffrey Reed

Peter (Yong) Lian

Thomas Robertazzi

Embedded Control for Mobile Robotic Applications

Leena Vachhani

Indian Institute of Technology

Bombay

Pranjal Vyas

Advanced Remanufacturing Technology Center Agency of Science

Technology and Research (A*STAR)

Singapore

Arunkumar G. K.

Indian Institute of Technology

Bombay

Copyright © 2022 by The Institute of Electrical and Electronics Engineers, Inc. All rights reserved.

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Preface

The book aims at the community interested in learning control design for targeting implementation on an embedded platform. The issues in implementing a controller on an embedded platform are usually not considered at the time of designing. This book first gives an overview of implementation issues and then gives its implication on controller performance. The control engineer must ensure that these implications do not disturb the stability of the control system and do not give performance deterioration due to the controller's embedded implementation.

The trend in mobile robotic applications is to use onboard processing and sensing, making the robot self-sufficient. With the objectives of onboard processing and sensing, the controller must guarantee control objectives set for the particular application. While the controller designed using theoretical concepts support the claims on selected control objectives for the robotic application, the faithful implementation of the designed controller is equally important to guarantee the execution of designed controller. Typical issues in embedded implementation are limited memory, limited data width, quantization noise, sampling noise, and limited computational capability. These implementation issues, if ignored, raise the question of stability of the designed controller. Hence, the analysis of controller design is incomplete without considering the issues in implementation. A way to deal with this is to ensure that these embedded implementation issues do not affect stability. The other better way is to consider the issues and limitations of an embedded processor when designing the controller. There is a need of considering the implementation aspects at the time of designing controller using control theoretical concepts.

The book presents the concepts and challenges in designing embedded controller for mobile robotic applications. The approach in this book is to give elementary concepts on embedded designs and use of control concepts for designing efficient embedded controllers for mobile robotic application. The question is now how to use the concepts in future controller designs. The answer lies in the approaches covered in the bottom-up (Chapter 4) and top-down (Chapter 5) approaches. These approaches are presented to provide generic methodologies for embedded controller designs. However, the general methodologies may not be limited to the ones covered in this book. The emphasis in this book is to develop embedded controller designs with a generic approach for catering to variety of control objectives in the larger set of mobile robotic applications. In particular, the book interlaces relevant control theory concepts with embedded design concepts applied to mobile robotic applications. The embedded controller design with a generic approach facilitates straightforward implementation. It is clear that the embedded controller design for mobile robotic applications must cover the topics on embedded design, controller design concepts, and mobile robotic applications. The book presents these concepts in a systematic interlaced manner.

Available embedded technologies and the corresponding design efforts to estimate the market value on embedded controller design are introduced in the first chapter. Further, the embedded technologies are mapped to popular embedded processors to date and their requirements and limitations from the controller design perspective.

The embedded controller is designed in discrete time as it requires digital implementation, while the operations of a practical system (mobile robot) are in continuous time. The approximate methods that can be used for designing controllers and ensuring stability are discussed in Chapter 2. Furthermore, possible effect of embedded implementation regarding sampling, quantization, and processing-time on stability and performance of controller design are discussed in detail.

The mobile robotic applications have a few basic operations or tasks to be implemented. These basic tasks are typically common among many applications. Chapter 3 discusses these common tasks which include 2D and 3D transformations, collision detection and avoidance, localization and navigation. Some of the multi-agent applications are also presented. The perspectives of control design are presented that cover the objectives of these tasks and the feedback collected through the sensors.

Having covered the embedded implementation requirements and objectives of various tasks in mobile robotic applications, two methodologies to design embedded controllers are discussed next. These are bottom-up and top-down. The bottom-up methodology covered in Chapter 4 targets the controller design for a specific embedded platform. In particular, the selection of an embedded platform is followed by the controller design. Alternatively, the top-down methodology designs the controller keeping in mind that it is realized on an embedded platform with limited resources. There is no specific way of designing embedded controllers using these methods; hence, the methodologies are illustrated by designing embedded controllers for robotic applications.

The last chapter of the book covers the embedded control design using Field Programmable Gate Array (FPGA). The FPGA is an embedded platform providing reconfigurability in hardware architecture. Lately, FPGAs have gained popularity, especially in robotic applications, due to their capabilities of parallel processing and multiple Input/Output (I/O) handling. Multiple I/Os do not limit the sensing/actuating dependencies and parallel architecture supports implementation of independent control loops. Basics of FPGA and a methodology to design FPGA architecture for a controller complete the discussion on embedded controller designs.

The target audience for this book are professionals working in embedded control design. The book presents applications of embedded control design to autonomous robotics. Hence, the robotic community would also use the concepts in this book for further control applications in robotics. The book is useful for both academicians and practitioners as it provides content on implementation aspects. The book will also be an excellent resource for designing courses on embedded control and robotics. It covers the discussion on various embedded platforms available in the market, their use in controller implementation, several issues in implementation, stability analysis of designed controller, and two new approaches for designing embedded controllers. Illustrations of these approaches demonstrate the embedded controller designs of typical robotic applications. A chapter on FPGA architecture development for controller design is also a good resource for practitioners. A course on robotics can cover the topics on embedded implementation issues, and controller design approaches discussed in this book.

LEENA VACHHANI

Mumbai, India

October 2021

Acknowledgments

We acknowledge our mentors, colleagues working in this field, students, friends, and family who have given direct and indirect support in completing this book. It is impossible to call this list complete as it would never be.

This book reflects the work of many past and present students in this field. We would especially like to acknowledge Anindya Harchowdhury, Anupa Sabnis, Aseem V. Borkar, Dhruv Shah, Maria Thomas, Misha Gupta, Mohit Chachada, Mukesh Agarwal, Nipun Agarwal, Nithin Xavier, Sarat Chandra Nagavarapu, Shantanu Thakkar, Shreyas S. G., Siddhesh Wani, Vikranth Reddy Dwaracherla, and Vivek Yogi. Special mention to IIT Bombay faculty working in this field with whom we had several formal and informal discussions. We wish to express our gratitude to Abhishek Gupta, Anirban Guha, Arnab Maity, Arpita Sinha, Bijnan Bandyopadhyay, Hemendra Arya, Kannan Maudgalaya, Ravi Banavar, Sachin Patwardhan, Sukumar Srikant, and P. S. V. Nataraj. Special thanks to K. Sridharan, and B. Ravi for mentoring and guiding Leena in her professional career. Pranjal thanks Leena Vachhani, K. Sridharan, and Sanjeev Kane for their constant support and guidance throughout his career.

We appreciate our most important support system, our friends, parents, and family members. Leena conveys gratitude to Deepak, Deeshan, Dinesh, and Divya for their love, dedication, and consent to sparing her family time on this book. Pranjal is thankful to his wife Hansini for her love, affection, motivation, and constant support during the book-writing phase. He credits his parents' love, blessings, and sacrifice for being in his current professional position.

We would also like to thank the IRCC, IIT Bombay, for providing seed support for initiating research in this field. We thank IIT Bombay for supporting embedded control lab development, DST-SERB, and NRB for their support through research grants.

This book has emerged as a compilation of lecture notes while conducting courses and improving the material based on the received feedbacks. However, when we started compiling our learnings from research and delivering course materials, we realized that it takes efforts more than envisioned to connect the concepts and correct the flow. Lastly, we are thankful to the IEEE-Wiley publishing house for having patience with us and providing feedback on the book proposal.

Acronyms

2D

2 Dimensional

3D

3 Dimensional

ADC

Analog-to-Digital Converter

ALU

Arithmetic and Logic Unit

ASIC

Application-Specific Integrated Circuit

CMR

Car-like Mobile Robot

CORDIC

Coordinate Rotation DIgital Computer

CPLD

Complex Programmable Logic Array

CVM

Curvature Velocity Technique

DAC

Digital-to-Analog Converter

DDMR

Differential-Drive Mobile Robot

DSP

Digital Signal Processor

DWA

Dynamic Window Approach

ECS

Embedded Control System

FPGA

Field Programmable Gate Array

FSM

Finite State Machine

FWSR

Front Wheel Steering Robot

HDL

Hardware Descriptive Language

I/O

Input/Output

IC

Integrated Circuits

IOB

Input–Output Block

LHS

Left-Hand Side

LiDaR

Light Detection and Ranging

LUT

Look Up Table

MPC

Model Predictive Controller

MSB

Most Significant Bit

ND

Nearness Diagram

NRE

Non-Recurrent Engineering

PID

Proportional-Integral-Derivative

PLA

Programmable Logic Array

PLD

Programmable Logic Devices

RHS

Right-Hand Side

RRT

Rapid Exploring Random Trees

SMC

Sliding-Mode Control

VFH

Vector Field Histogram

VLSI

Very Large-Scale Integration

WSN

Wireless Sensor Network

ZoH

Zero-order-Hold

Introduction

An embedded system provides support for sensor interfacing, processing, storing, and/or controlling to facilitate compact and customized solutions. Embedded systems have wide range of applications such as entertainment, communication, security, and automobile. This book focuses on using embedded technology for control system. Targeting the entire control design on an embedded system has many advantages like better performance, portability, optimized area-time ratio, less power requirement, better life, etc. An embedded control system is designed to perform a specific task; therefore, it can optimize on requirements of power, area, and time. Some of the areas where embedded control-systems can replace the traditional control-systems are flight systems, process-control, automobile, and automation industries. Traditional control systems use general-purpose processors. Although the design using traditional control system has flexibility, it cannot be optimized further. The embedded control systems overcome this drawback and can be designed to optimize for area, power, computation time, and accuracy.

There exist many embedded technologies and selecting a right kind of embedded platform from those available in market is another main concern. This selection will affect the performance, power requirement, and life of the control system. Building an embedded control system for a specific application is an intense task. The stand-alone embedded control system has to broadly perform following sub-tasks at every sample instance:

Process the sensor data (collected as state variables) and extract feedback information from it.

Compute the control input using a control strategy.

Issue the commands to the actuators in order to bring the system to next state.

The requirements of the application in terms of its real-time capability, performance in digital world, computation efficiency, etc. have to be studied before choosing the right embedded platform. Techniques for using this embedded platform have to be intensely studied in order to utilize full power of that platform. There are many issues and challenges to be addressed while implementing a control design on an embedded platform. These issues are as small as digital resolution and as big as real-time requirements. Furthermore, the embedded implementation of control system design must ensure stability and, therefore, there is a need to know simple techniques for guaranteeing that the stability analysis has no effect with embedded implementation. The end product of embedded solution for a control design is an optimized hardware.

The embedded control design for a specific application can target an embedded platform and explore its benefits for controller design and implementation. In this book, we describe the controller designs for mobile robotic applications; hence, following learning objectives and corresponding motive are set addressing a generic approach to design and implement embedded controllers for mobile robotic applications:

Study of design concepts and popular embedded technologies to know the available benefits and limitations through embedded implementations.

Understanding existing mobile robot models for representing system for controller designs.

Learn methods to obtain approximated discrete-time representation for control system. The methodology emphasizes on simple tools to ensure stability analysis is not affected by the embedded implementation.

Knowledge of a few primitive tasks that are needed for most of the robotic applications helps in forming control objectives.

The aim of relating the control objectives to the embedded requirements and satisfying the same develops two methodologies. Learning these bottom-up and top-down methodologies using the examples of primitive tasks builds up the techniques for developing embedded controllers for mobile robotic applications.

For exploiting the benefits of parallel hardware architecture in

field programmable gate array

(

FPGA

) in mobile robotic applications, learn a systematic way to implement embedded controller using specific examples.

In order to satisfy the learning objectives, the chapters are organized as follows: Chapter 1 presents the overview of embedded control system followed by kinematic models of 2D and 3D mobile vehicles to develop system model. The design cost involved in embedded controller development is discussed. Various popular commercially available embedded platforms with their limitations and benefits are then addressed. As the controller implemented on an embedded platform performs digital computations, the discrete-time control concepts are covered in Chapter 2. Since the system model (mobile robot) is operating in continuous-time and controller is executed in discrete-time, the corresponding interfaces are discussed and approximate methods that ensure stability are presented. In Chapter 3, the primitive tasks required for most of the mobile robot applications are studied. Chapters 4 and 5 now describe embedded controller designs for a few primitive tasks and high-level mobile robotic applications covering a generic approach so that controller designs for emerging applications ensure stability and satisfy control objectives. The emerging mobile robotic applications demand for real-time operations with multiple control loops. These requirements can be easily fulfilled by the parallel hardware architecture designs in FPGA. A generic method to design parallel hardware for embedded control is studied in Chapter 6. This book is then summarized in Chapter 7.

About the Companion Website

This book is accompanied by a companion website:

www.wiley.com/go/vachhani/embeddedcontrolforroboticapp

The website include:

Codes.

1Embedded Technology for Mobile Robotics

Mobile robot applications are popular in various domains such as security, surveillance, automation, agriculture, and space missions. While the autonomy and capability to perform complex tasks are being possible, it is always required to control the robot operations including low-level control of actuators and processing sensors. It is increasing demand of accommodating all the controls and processing on an embedded system to optimize power consumption, size, and/or cost. The performance of a robotic system not only depends on the attached sensors but also its controller design. Further, the implementation of controller and processing sensors largely contribute to the desired behavior of the robot. Hence, a great deal of importance is to be given for implementation aspects of the controller.

The embedded system solution provides a customized solution for a controller. This customization may target optimization for cost, power, size, speed, or combination of these. Furthermore, the controller on an embedded platform may be designed to achieve real-time requirements. A single platform may be used for multiple controllers working in synchronization. The synchronization or parallel triggering is easily achievable if the architecture for the controllers is designed on a single chip using either Application-Specific Integrated Circuit (ASIC) or Field Programmable Gate Array (FPGA) technology. However, one needs to learn designing architecture to best utilize these technologies.

There exists availability of cross-platforms like system generator