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University Robotics Theory & Algorithms

Modern Robotics: Mechanics, Planning, and Control

Complete breakdown of the acclaimed 6-course Northwestern University specialization by Prof. Kevin M. Lynch and Frank C. Park (Cambridge University Press). Free to audit.

Instructor: Prof. Kevin M. Lynch Institution: Northwestern University Simulation: CoppeliaSim / Python / MATLAB Book: Free Textbook PDF ↗

The 6-Course Curriculum Overview

Course 1: Foundations of Robot Motion (Chapters 2 & 3)

Mathematical descriptions of spatial configuration and velocity:

  • Configuration Space (C-space): Topology, holonomic and nonholonomic constraints, Grubler’s formula for degrees of freedom (DoF = m(N-1-J) + sum(f_i)).
  • Spatial Rigid-Body Motions: Rotation matrices SO(3), exponential coordinates of rotation, and Rodrigues' formula.
  • Twists & Screws: Homogeneous transformation matrices SE(3), spatial and body twists, screw axes, and spatial wrenches.

Course 2: Robot Kinematics (Chapters 4, 5, 6, 7)

Modern screw-theoretic formulation of kinematics bypassing traditional DH parameters:

  • Product of Exponentials (PoE) Formula: Forward kinematics using exponential screw matrix products.
  • Velocity Kinematics & Manipulator Jacobian: Body Jacobian and space Jacobian. Kinematic singularities and manipulability ellipsoids.
  • Numerical Inverse Kinematics: Newton-Raphson method and damped least-squares (Levenberg-Marquardt) using the pseudoinverse.

Course 3: Robot Dynamics (Chapters 8 & 9)

Equations of motion for open-chain robot arms:

  • Newton-Euler Inverse Dynamics: Forward-backward recursive algorithm calculating motor torques in O(n) time.
  • Euler-Lagrange Forward Dynamics: Simulating joint accelerations using mass matrix inverse.
  • Trajectory Generation: Quintic polynomials, trapezoidal velocity profiles, and time-optimal path parameterization.

Course 4: Robot Motion Planning and Control (Chapters 10 & 11)

  • Motion Planning: Sampling-based planners: Rapidly-exploring Random Trees (RRT, RRT*), Probabilistic Roadmaps (PRM), and Artificial Potential Fields.
  • Motion Control: Computed torque control, task-space error dynamics, feedforward control, and Passivity-based PID.

Course 5: Manipulation & Mobile Robots (Chapters 12 & 13)

  • Contact Kinematics & Grasping: Friction cones, form closure, force closure, and rolling contact equations.
  • Wheeled Mobile Robots: Kinematics of differential drive robots, unicycle models, car-like robots, and omnidirectional Mecanum bases.

Course 6: Capstone Project (Mobile Manipulation)

Program a simulated KUKA youBot (mobile base + 5-DOF arm) inside CoppeliaSim to autonomously drive to a standoff position, grasp a block, transport it across obstacles, and place it at a goal orientation using feedforward plus PI feedback control.

Direct Code Repository

The official Python, MATLAB, and Mathematica code libraries implementing all algorithms from the book are hosted on GitHub:

Explore NxRLab/ModernRobotics on GitHub ↗