This module introduces PD control methods, emphasizing control partitioning and effective motion control. Key topics include:
Students will learn about practical applications and the significance of control techniques in robotics.
This module provides an overview of the course, including the history of robotics and its applications. It highlights related courses at Stanford and outlines essential topics such as manipulator kinematics and dynamics.
Key areas covered include:
This module focuses on spatial descriptions essential for understanding robotic movements. It covers generalized and operational coordinates, rotation matrices, and translations.
Students will learn about:
Examples will illustrate these concepts to solidify understanding.
This module delves into homogeneous transform interpretations, focusing on compound transformations and rotation representations. Key topics include:
Examples will enhance understanding of these fundamental concepts in robotics.
This module introduces manipulator kinematics, outlining link descriptions and connections using Denavit-Hartenberg parameters. Topics covered include:
Students will learn to construct the Denavit-Hartenberg table and apply it to robotic systems.
This module summarizes frame attachment, providing practical examples such as the RPRR manipulator and the Stanford Scheinman Arm. Topics include:
Understanding these concepts is vital for effective manipulator control.
This module covers instantaneous kinematics, focusing on the Jacobian matrix and its applications. Key topics include:
Examples will help students grasp the application of Jacobians in robotic systems.
This module presents the explicit form of the Jacobian. Students will explore:
Examples will demonstrate the significance of Jacobians in robotic systems and their applications in motion control.
This module features a demo of the Scheinman Arm, emphasizing kinematic singularities and their implications. Topics include:
Examples illustrate the importance of understanding these concepts in real-world robotic applications.
This module introduces guest lecturer Gregory Hager, who discusses computer vision and its application in robotics. Topics include:
Students will also learn about tracking cycles and future challenges in computer vision technology.
This module features guest lecturer Krasimir Kolarov, who addresses trajectory generation in robotics. Key topics include:
Students will learn about trajectory planning with obstacles and its significance in robotic applications.
This module focuses on joint space dynamics, introducing the Newton-Euler algorithm and inertia tensor calculations. Topics include:
Examples will illustrate the application of these equations in robotic systems.
This module elaborates on Lagrange equations, focusing on deriving equations of motion and understanding kinetic energy. Topics include:
Students will learn about the final equation of motion and its applications in robotics.
This module provides an overview of control systems used in robotics. Key topics include:
Examples will illustrate how different control techniques can be applied to robotic systems.
This module introduces PD control methods, emphasizing control partitioning and effective motion control. Key topics include:
Students will learn about practical applications and the significance of control techniques in robotics.
This module focuses on manipulator control, covering stability and task-oriented control strategies. Key topics include:
Examples demonstrate how these concepts are applied in robotic systems.
This module discusses compliance in robotic systems, highlighting the importance of force control and dynamics. Topics include:
Students will learn about the Stanford Human-Safe Robot and its implications for robotics.