Optimization for Robot Modelling with MATLAB

✍ Scribed by Hazim Nasir Ghafil, Károly Jármai

• Publisher: Springer
• Tongue: English
• Leaves: 229
• Category: Library

✦ Synopsis

This book addresses optimization in robotics, in terms of both the configuration space and the metal structure of the robot arm itself; and discusses, describes and builds different types of heuristics and algorithms in MATLAB.

In addition, the book includes a wealth of examples and exercises. In particular, it enables the reader to write a MATLAB code for all the related problems in robotics. The book also offers detailed descriptions of and builds from scratch several types of optimization algorithms using MATLAB and simplified methods, especially for inverse problems and avoiding singularities. Each chapter features examples and exercises to enhance the reader’s comprehension. Accordingly, the book offers the reader a better understanding of robot analysis from an optimization standpoint.

✦ Table of Contents

Preface
Acknowledgements
About this Book
Contents
About the Authors
1 Introduction
1.1 Background
1.2 Why Optimization?
1.3 Application of Optimization in the Industrial Robot Arm
1.3.1 Grinding and Polishing
1.3.2 Cutting
1.3.3 Assembly
1.3.4 Painting
1.3.5 Welding
1.3.6 Optimization and Robot Design
1.3.7 Optimization and Robot Configuration Space
1.4 About This Book
1.5 Who Read This Book?
1.6 Outline
1.7 Teaching with This Book
References
2 Optimization
2.1 Introduction
2.2 Ant Algorithm
2.2.1 Ant System
2.2.2 Ant Colony System (ACS)
2.2.3 Ant Colony Optimization for a Continuous Domain
2.3 Flower Pollination Algorithm
2.4 Invasive Weeds Optimization
2.5 Bacterial Foraging Optimization
2.6 Bat Algorithm (BATA)
2.7 Bees Algorithm (BA)
2.8 The Cross-entropy Method
2.9 Cuckoo Search (CS)
2.10 Cultural Algorithm
2.11 Differential Evolution
2.12 Firefly Algorithm
2.13 Harmony Search
2.14 Memetic Algorithm
2.15 Nelder–Mead
2.16 Particle Swarm Optimization
2.17 Multiswarm Optimization
2.18 Random Search
2.19 Simulated Annealing
2.20 Practical Examples
2.20.1 Particle Swarm Optimization (Eberhart and Kennedy 1995)
2.20.2 Artificial Bee Colony
2.21 Summary
References
3 Spatial Representations
3.1 Introduction
3.2 Position Representation
3.3 Rotation Matrix
3.3.1 Properties of the Rotation Matrix
3.4 Composition of Rotations
3.5 Euler Angles
3.6 Roll, Pitch, and Yaw Angles
3.7 Homogenous Transformation Matrix
3.8 Summary
Exercises
4 Manipulator Kinematics
4.1 Introduction
4.2 Manipulator
4.2.1 Link
4.2.2 Joints
4.2.3 End-Effector
4.2.4 Configuration
4.2.5 Configuration Space
4.2.6 Singularity
4.2.7 Cartesian Space
4.2.8 Joint Space
4.3 Kinematic Chain: Forward Kinematics
4.4 Denavit–Hartenberg (DH) Convention
4.5 Inverse Kinematics
4.5.1 Objective Function
4.6 Summary
Exercises
References
5 The Manipulator Jacobian
5.1 Introduction
5.2 Velocity of a Point
5.3 Skew-Symmetric Matrix
5.3.1 Properties of Skew-Symmetric Matrix
5.4 Angular Velocity
5.5 Angular Velocity of a Kinematic Chain
5.6 Linear Velocity
5.7 The Jacobian
5.8 Inverse Acceleration and Velocity
5.9 Additive to the Jacobian
5.10 Summary
Exercises
6 Path and Trajectory Planning
6.1 Introduction
6.2 Path Planning
6.3 Ant Colony Optimization for TSP
6.4 Cubic Spline Curves
6.5 Collision Detection
6.6 Addition to Collision Detection
6.7 Trajectory Planning
6.7.1 Point-to-Point Trajectory
6.7.2 Via-Point Trajectory
6.8 Summary
Exercises
References
7 Dynamics
7.1 Introduction
7.2 Euler–Lagrange Equations
7.3 Rigid Links
7.4 Dynamic Equations for n-DOF Manipulator
7.5 Inertia Tensor
7.6 Discussion
7.7 Summary
Exercises
Reference
8 Structural Optimization and Stiffness Analysis
8.1 Introduction
8.2 Structural Optimization
8.2.1 Structural Optimization of a 7DOF-Type Robot
8.3 Stiffness Analysis
8.4 Lumped Parameter Model
8.4.1 Method Based on Joint Compliance
8.4.2 Method Based on Joints and Links Compliants
8.5 Matrix Structural Analysis
8.5.1 Stiffness of Link and Joint
8.5.2 Methodology
8.6 Summary
Exercises
References
9 Kinematic Synthesis
9.1 Introduction
9.2 Type Synthesis
9.3 Dimensional Synthesis
9.4 Genetic Algorithms
9.5 Genetic Representation of a Mechanism
9.6 Graph Theory
9.6.1 Graph
9.6.2 Incidence
9.6.3 Adjacent Vertices
9.6.4 Adjacent Edge
9.6.5 Self-loop
9.6.6 Parallel Edge
9.6.7 Incidence Matrix
9.7 Liu Approach
9.8 Planning Method
9.9 Discussion on Planning Method
9.10 Summary
References
Index