A Student Guide to AI and Robotics With Real-World Case Studies and Programming Examples

Preface
About the Authors

Part I Foundations of Intelligent Systems
Chapter 01 Understanding Embodied Intelligence
Chapter 02 Mathematical Thinking for Intelligent Systems
Chapter 03 Patterns, Logic, and Thinking Like a Computer
Part II Programming and Software Systems
Chapter 04 Programming Smart Agents
Chapter 05 Software Engineering for Robotics
Chapter 06 Securing Robotic Systems
Part III Building and Controlling Robots
Chapter 07 How Robots Are Built: Form, Function, and Failure
Chapter 08 Control and Feedback in Robotics
Part IV Perception and Autonomy
Chapter 09 Vision and Sensing: Perception in Motion
Chapter 10 Navigation and Mapping the Unknown
Chapter 11 Adaptive and Learning Robots
Part V Humans, Ethics, and Systems Thinking
Chapter 12 Human–Robot Interaction
Chapter 13 Ethical and Responsible Robotics
Chapter 14 Project Management for Robotics Systems
Part VI The Future of Intelligence
Chapter 15 Innovation, Futures, and Hybrid Intelligence

Biography

Mahwish Zahara is an artificial intelligence lecturer, published author, and guest speaker, specialising in marketing strategy, data science, and applied artificial intelligence (AI). She designed and launched one of the UK’s first ever Masters courses in AI in Marketing which enabled students to learn machine learning workflows, advanced data applications, and how to apply them to real world business problems.

An expert in marketing strategy with a PhD in Business and Marketing. Her research explores the intersection of digital technologies and marketing, with a focus on generative AI, marketing automation, consumer insights and algorithmic decision-making. Through her research and teaching she embeds new technologies into the learning journey to develop technical and critical thinking skills for the AI enabled future global economy.

Contributing curriculum design and innovation at academic and commercial levels, developing frameworks for ethical and strategic use of large language models for teaching and research outputs. Delivering hands on experience and an industry-facing approach to learning, her students gain experience with AI model programming workflows, large model architectures, and cloud-based computing platforms whilst developing critical thought around their limitations, metrics for performance and real-world applicability.

Investigating frontier technologies like quantum computing, AI-driven robotics and the next generation of intelligent systems. With recent publications and editing AI in Marketing texts on AI-powered customer experience, conversational AI, and ethics of AI in marketing. Dr Zahara continues to contribute to innovation at the forefront of AI and marketing.

Tamour Raza conducts research around Artificial Intelligence and Robotics engineering, specialising in machine learning, algorithmic decision-making, and designing intelligent socio-technical systems. His work has covered both theoretical and computational principles for supervised and unsupervised learning; prediction; optimisation-based decision-making and modelling systems that learn through feedback commonly used in robotics and autonomous systems.

He is particularly interested in how intelligent systems behave at scale, deployed in intricate settings defined by uncertainty, variability, real-time operations, and large, heterogeneous end-users. Tamour explores system performance, robustness and adaptation, while considering broader implications such systems have when deployed at scale.

Tamour’s previous academic research has surrounded artificial intelligence systems within industry sectors, publishing papers around algorithmic systems in marketing and how technologies such as recommender systems, customer intelligence models and real-time decision engines affect organisational decision-making processes and end-user experiences. He is the co-author of AI textbook A Student Guide to AI and Robotics which closely ties his research to real world applications.

Tamour takes a socio-technical approach to his research and considers alongside raw technical performance metrics of machine learning systems how they may be used at an organisational level and what their broader ethical and societal consequences are. He aims to design systems that are rigorous, interpretable, and accountable.

Obianuju Blossom Ochuba specializes in Robotics and Artificial Intelligence with a focus on intelligent systems, automation, and data-driven solutions. She graduated with a Master of Science degree in Robotics and Artificial Intelligence as well as a degree in Electrical and Electronic Engineering.

She has experience in robotic perception, adaptive control, automation, and intelligent data systems. She also possesses knowledge in programming and algorithm development which she has utilized while working in technical and analytics roles in the industry. She has worked on projects involving automation pipelines, data systems/architecture, and AI driven decision-making systems.

Her expertise includes building and testing smart systems in real-world scenarios. She's always curious about how well these systems perform and how they can be scaled. Obianuju often implements her work from an engineering standpoint and an applied standpoint as she loves to understand the theory behind practical implementations. She's passionate about creating and helping to build robust and scalable AI systems as well as helping technology function in complex real-world scenarios.