before getting into robotics, strengthen your math. robotics is applied mathematics running on motors. without the math, you are wiring components and copying code. linear algebra • vectors and coordinate frames • matrix multiplication • eigenvalues, eigenvectors • transformations and rotations (SO(3), SE(3)) every pose estimate, every sensor fusion step, every neural network layer is linear algebra. calculus • derivatives as rates of change • integrals as accumulation • differential equations • gradients and optimization control systems are calculus. trajectory generation is calculus. learning algorithms are calculus. probability and statistics • random variables and distributions • bayes’ rule • expectation and variance • gaussian noise models real sensors are noisy. state estimation is probabilistic. kalman filters, particle filters, SLAM; all statistics. tools like ROS 2 and Gazebo are interfaces. the math is the substance....