Linear Algebra
Vectors, matrices, eigenstuff — the language of robotics.
easyFoundations
Why it matters in robotics
Linear algebra is the literal language of robotics: every rigid-body pose, rotation, camera projection, and state estimate is a vector or matrix operation, so interviewers probe it constantly. Expect to derive rotation and transformation matrices, reason about a matrix's rank and null space (e.g. for Jacobian singularities), and explain eigenvalues and SVD in the context of stability, least-squares, or covariance. Fluency here is assumed before any kinematics, controls, or SLAM question.
Application focus
The same topic, tailored to the robot you're building. Your choice is remembered across the roadmap and every topic.
Select an application above.
What to study
- ✓Vectors, matrix multiplication, and linear transformations as geometric operations (rotation, scaling, projection)
- ✓The four fundamental subspaces: column space, null space, rank, and what they imply about Ax = b solvability
- ✓Eigenvalues, eigenvectors, and diagonalization — the basis of stability analysis and principal directions
- ✓Orthogonality, least-squares, and the SVD for solving overdetermined systems and low-rank approximation
Study by time budget
Pick the path that fits the time you have before your interview.