The definitive textbook on motion planning, decision-theoretic planning, and planning under differential constraints. All 15 chapters rebuilt as interactive lessons.
What does "planning" mean? State, time, actions, plans vs policies. The four parts of the book.
State spaces, BFS/DFS, value iteration, Dijkstra, A* search. The algorithmic foundations.
Rotation matrices, homogeneous coordinates, DH parameters, forward kinematics.
Topology, SE(2)/SE(3), C-space obstacles, Minkowski sums. The unifying abstraction.
RRTs, PRMs, collision detection, Voronoi bias. Real-world motion planning.
Visibility graphs, cell decompositions, algebraic geometry. Exact algorithms.
Time-varying, multi-robot, manipulation, coverage, optimal planning (RRT*).
Vector fields, potential fields, navigation functions, sampling-based feedback.
Games against nature, minimax, zero-sum games, Nash equilibrium, Prisoner's dilemma.
MDPs, value/policy iteration, Q-learning, sequential game theory.
Sensors, I-states, belief updates, Kalman filters, particle filters.
Localization, mapping, SLAM, pursuit-evasion, exploration.
Velocity constraints, nonholonomic systems, Newton-Euler, Lagrangian mechanics.
Kinodynamic RRT, trajectory optimization, decoupled approaches.
Controllability, HJB, Dubins/Reeds-Shepp paths, Lie brackets, steering methods.