Dynamics
Forces, torques, equations of motion.
Why it matters in robotics
Dynamics is where control interviews get hard: you're expected to write the manipulator equation M(q)q̈ + C(q,q̇)q̇ + g(q) = τ from memory and explain what every term physically means. Interviewers probe whether you understand the difference between forward and inverse dynamics, why the mass matrix is configuration-dependent and symmetric positive-definite, and how these equations underpin model-based control like computed-torque and gravity compensation. Getting the structure and intuition right signals you can actually model and control a real robot, not just recite kinematics.
Application focus
The same topic, tailored to the robot you're building. Your choice is remembered across the roadmap and every topic.
At a glance
The manipulator equation links joint torques to motion; reading it one way gives inverse dynamics, the other way forward dynamics.
What to study
- ✓Lagrangian formulation: deriving equations of motion from kinetic minus potential energy (d/dt(∂L/∂q̇) - ∂L/∂q = τ)
- ✓The manipulator equation and its terms: mass/inertia matrix M(q), Coriolis/centripetal C(q,q̇), and gravity g(q)
- ✓Recursive Newton-Euler algorithm for efficient inverse dynamics (forward/backward iterations)
- ✓Forward vs. inverse dynamics and their use in simulation and model-based control (computed-torque, gravity compensation)
Study by time budget
Pick the path that fits the time you have before your interview.