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About the Book

Mathematics for Robotics

By Satyam Mishra, Dr. Vishwanath Bijalwan, Dr. Vijay Bhaskar Semwal, and Ms. Phung Thao Vi

Unlock the Mathematical Foundations Behind Robotic Intelligence.

This book isn't just about formulas: it's about building the brain behind the machine. Mathematics for Robotics is your essential guide to understanding the core mathematical tools that power modern robotics, from coordinate geometry and vector calculus to probability and control theory.

Whether you're a student diving into robotics for the first time, a researcher brushing up your foundations, or an engineer building intelligent systems, this book offers:

✔️ Clear, structured explanations of core math concepts

✔️ Robotics-focused applications of each topic

✔️ Visual diagrams and intuitive analogies

✔️ Practice examples that link theory to real-world movement

Crafted by a passionate team of educators and researchers from diverse fields, this book turns abstract mathematics into tangible robotic insight. You'll walk away not just knowing the math: but understanding why it matters and how to apply it.

Perfect for:

Robotics enthusiasts • Engineering students • AI and ML learners • Educators bridging math and tech

Take the leap from math to motion. Let your robots think: mathematically.


About the Author

Satyam Mishra’s avatar Satyam Mishra

@satyam_cser

Instagram

If AI had a dating profile, Satyam Mishra would probably be the person it swipes right on. With 5+ years of wrangling code, math, and GPUs (sometimes successfully), he’s been building everything from GPT-powered autonomous agents to robots that can navigate the world without bumping into walls… most of the time.

Specialties? Oh, just the casual stuff: Generative AI, Machine Learning, Computer Vision, Embedded Systems, and Agentic AI. Recently, he’s been flirting with LLM optimization, Koopman-based AI (yes, it’s as fancy as it sounds), optical computing (optical neural networks), and making AI explain why it does what it does without sounding like a politician.

Projects? He’s rolled out grammar-constrained reinforcement learning (because even AI needs to mind its language), fine-tuned LLMs with RAG systems, built contactless facial authentication (so you can look at your computer and it just knows), and cooked up personalized LMS/ERP platforms that make both students and managers slightly less stressed.

He’s also been the brains behind KoopFormer (a physics-inspired transformer that teaches AI motion synthesis, still in progress work) and NeuroExplain (an LLM that talks neuroscience without melting your brain, still in progress work). On the ops side, he’s deployed secure hybrid AI platforms with K3s, Vault, Prometheus, and GitOps: basically making AI run like a well-oiled (and well-guarded) machine.

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