Buch, Englisch, 700 Seiten, Format (B × H): 152 mm x 229 mm
Buch, Englisch, 700 Seiten, Format (B × H): 152 mm x 229 mm
ISBN: 978-0-443-30106-3
Verlag: Elsevier Science
Modeling, Dynamics and Control approaches for Modern Robotics explores and investigates various theoretical and practical principles related to modeling, dynamics, and control in robotics. The objective is to enhance the understanding and development of robotic systems by applying these principles. Through accurate representations of robot kinematics and dynamics, researchers aim to effectively analyze and predict robot behavior. This title focuses on designing algorithms and control strategies for precise and efficient robotic system management.
Additionally, the book delves into sensory feedback and perception systems for robots, advancements in autonomous vehicles, industrial automation, humanoid robots, and medical robotics, showcasing the integration of technology and computing power in modern applications. The study of control approaches and the development of optimized performance schemes are highlighted, demonstrating the significance of stability and adaptive response in changing environments. This comprehensive examination underscores the evolution and complexity of robotic systems, emphasizing their growing role in various sectors.
Autoren/Hrsg.
Fachgebiete
- Technische Wissenschaften Maschinenbau | Werkstoffkunde Maschinenbau
- Technische Wissenschaften Technik Allgemein Technik: Allgemeines
- Technische Wissenschaften Elektronik | Nachrichtentechnik Elektronik Robotik
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
- Technische Wissenschaften Energietechnik | Elektrotechnik Elektrotechnik
Weitere Infos & Material
1. Control Systems Principles
2. Kinematics and Dynamics
3. Sensors and Actuators control
4. System Architectures
5. Trajectory planning of a mobile robot with obstacle avoidance using conventional methods and heuristic methods
6. Hardware Implementation of a Neuro-fuzzy Controller for robotic Manipulators
7. Computed Torque Control of the PUMA 560 Robot
8. Developing Medical Robotics with AI-Enhanced Biosensors
9. Visualisation of 3D trajectory control of drones using computer aided modelling.
10. Proportional-Derivative control for nonlinear robot dynamics using adaptive finite-time approach
11. Disturbance observer based sliding mode control with fixed-time convergence for perturbed robotic manipulators
12. Drone-based image processing to detect palm tree diseases
13. Model-Based Control Strategies
14. Optimal Control Approaches
15. Robust Control Strategies for Robotics
16. Advances in Medical Robotics
17. Explainable AI for Robotics
18. Reinforcement Learning for Robotics
19. Deep Reinforcement Learning for Robotics
20. Ethics for Robotics