Meet the editor

Dr. Martínez is a full professor at Universidad Autónoma de Ciudad Juárez since 2007; he founded and currently leads the robotics laboratory and the academic body of mechatronics at the Institute of Engineering and Technology. He received a BSc in computing engineering systems and an MSc in electronics engineering. Professor Martínez obtained his Ph.D. in robotics engineering from the University of Tsukuba, Japan in 2005.

He worked as a research fellow for Nanyang Technological University, Singapore (2005–2007) and as a postdoctoral fellow at Advanced Materials Research Center, Mexico (2007–2008). His research interests are dynamics modeling and control of robots, planning and navigation, scientific computing for bio- and neuro-robotics systems, sensors and actuators, and control of mechanisms and machines.

Contents

**Section 1**

Aerial Vehicles

Line Inspection

**Section 2**

**Section 3**

*and Valeri Kroumov*

and "Sampling Based Planner"

*and Eman H. Alkhammash*

*by Zahra Elmi and Soheila Elmi*

Rolling Biped Polynomial Motion Planning

**Preface XI**

Aerial Path Planning and Tracking **1**

**Chapter 1 3**

**Chapter 2 23**

AI-Based Optimization for Planning **43**

**Chapter 3 45**

**Chapter 4 61**

Wheeled Robots Planning and Control **79**

**Chapter 5 81**

**Chapter 6 97**

Recent Developments in Path Planning for Unmanned

Tracking Control of Unmanned Aerial Vehicle for Power

The Relationship between "C-Space", "Heuristic Methods",

A Survey on Recent Trends of PIO and Its Variants Applied

Autonomous Vehicle Path Planning Using MPC and APF

*by Santiago de J. Favela Ortíz and Edgar A. Martínez García*

*by Kenta Takaya, Hiroshi Ohta, Keishi Shibayama* 

*by Emanuele Sansebastiano and Angel P. del Pobil*

for Motion Planning of Dynamic Agents *by Muhammad Shafiq, Zain Anwar Ali* 

*by Abdul Majeed and Seong Oun Hwang*

## Contents


Preface

Motion planning is an interesting and inherent area in most robotics research and development. It ranges from a local motion control of a single actuator to a complex mobile machine compounded of sophisticated capabilities, such as path generation, trajectory tracking, global autonomous navigation, wide-space coverage for inspection and exploration, and local or global pathfinding in unknown environments. This book has organized a selection of recent advances in chapters divided by three general perspectives: a) aerial path planning and tracking, b) artificial intelligence (AI)-based optimization for planning, and c) wheeled robots planning and control. The chapters present specific planning works, essentially on estimation, prediction, optimization, observation, and

The first section introduces concepts and methods for unmanned aerial path planning and tracking that are critical for prospective new complex paradigms that contribute to the continued resilience of airspace coverage and applications

The second section presents AI approaches, heuristic and meta-heuristic optimization solutions for planning. Heuristic methods are problem-solving algorithms that emulate human thinking. Traditional graphical maps used for path planning when combined with heuristic approaches perform faster than some deterministic solutions, providing feasible paths. Moreover, optimization algorithms inspired by biological entities show fast convergence and efficiency in estimating locomotion for dynamic robotic agents. Bioinspired methods might perhaps solve multi-objective optimization problems, multi-robot path planning, formation control, and self-organization of distributed systems.

The third section treats one of the most traditional types of robotic platforms, the wheeled robots, which rely on a wide range of navigation control techniques. Wheeled vehicles depend on path planning and tracking to reach certain autonomy when facing the environmental dynamics to which they are subjected to. Local planning performance is critical due to multiple unpredictable obstacles in order to attain safe and suitable pathways for self-driving vehicles. A robotic platform depends on its kinematic mobility constraints to considerably perform path following. Longitudinal and lateral controls are required to efficiently track complex polynomial routes. Some mechanical structure designs depend on active and passive motions (e.g., limb bar linkage), where numerous analytical solutions are dominated by algebraic and derivative methods to model dynamic local planning considering obstacles, goals, and routes,

Finally, I would like to acknowledge the author service manager Ms. Sara Debeuc for her editorial support to complete this book. Additionally, I would like to thank

control in dynamic scenarios.

simultaneously.

performed by unmanned aerial vehicles.
