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Total Size:
13.6 MB
Info Hash:
69F8B908BF2E3FD703462CCA3A011C670EC98902
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Added:
April 18, 2026, 1:23 p.m.
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(Last updated: April 18, 2026, 1:24 p.m.)
| File | Size |
|---|---|
| Zeming F. Robotics Integrated Design And Practice 2026.pdf | 13.6 MB |
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SOURCE: Zeming F. Robotics Integrated Design And Practice 2026
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MEDIAINFO
Textbook in PDF format This book introduces the integrated design and practice for both serial robots and parallel robots as well as mobile robots. The design and construction of a robot with complete obstacle avoidance functions is introduced step by step, starting by introducing the working principles and knowledges on intelligent sensing, autonomous positioning and navigation, motion and control technologies, and then the robot control system and components. The main purpose of this book is to guide students to apply their theoretical knowledge onto practical robot design and constructions, and to enhance their interests in learning new knowledge and new technology. This approach cultivates the ability of the students to practice their skills, independent thinking and teamwork. With thorough study, students may come to understand the theoretical knowledge of robotic systems and master the abilities of comprehensive engineering design, which would help lay a solid foundation for their future career development. In recent years, target detection algorithms have made great breakthroughs. The more popular algorithms can be categorized into two groups: one is the candidate box-based R-CNN family of algorithms (R-CNN, Fast R-CNN, and Faster R-CNN), which require heuristics (selective search) or CNN networks (RPN) to generate candidate boxes first, followed by classification and regression on those candidate boxes. And the other category includes YOLO and SSD. One-stage algorithms, such as YOLO and SSD, use only one CNN to directly predict the categories and locations of different argets. The first class of algorithms is somewhat more accurate but slower, while the second class of algorithms is faster but less accurate. Distinguishing features of this book include the following: industry-aligned practicality — detailed case studies spanning design conception to functional implementation; multidisciplinary integration — seamless combination of mechanical engineering principles with computational techniques; progressive learning system — chapter-end exercises ranging from theoretical derivations to real-world simulation projects; digital resources — QR-code accessible supplementary materials including CAD models and MatLAB/Python codebases. This book is characterized by the combination of theory, engineering design and practice, and it is especially suitable for both senior undergraduate and postgraduate students majoring in robotics. It is also suitable for those scientific and technological researchers engaged in the fields of robot research, development, and application
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