Humanoid & Bipedal Robotics Roadmap
The cutting edge: 20+ DOF humanoid kinematics, Zero Moment Point (ZMP), Whole-Body Control, and Reinforcement Learning.
Explore the frontiers of humanoid and legged robotics. Master bipedal kinematics, dynamics, inverted pendulum gait models, Zero Moment Point (ZMP) stability, Whole-Body Impulse Control (WBIC), and Deep Reinforcement Learning with Isaac Gym.
Roadmap Curriculum & Milestones
Complete each sequential phase to build production-grade robotics competencies.
Phase 1: Bipedal Mechanics & Balance Foundations
Understand Center of Mass (CoM), Center of Pressure (CoP), Zero Moment Point (ZMP), and Linear Inverted Pendulum Model (LIPM).
Linear Inverted Pendulum Model (LIPM) & ZMP Preview Control
Formulate walking gait footstep placements using the 3D-LIPM and generate stable CoM trajectories with Kajita ZMP preview control.
- Zero Moment Point (ZMP) Criterion
- Linear Inverted Pendulum Model
- Cart-Table Model & Preview Control
- Footstep Planner
- Dynamic bipedal walking trajectory generator in Python
Phase 2: Whole-Body Control (WBC) & Contact QP Solvers
Resolve simultaneous hierarchical task objectives: balance, torso orientation, swing foot tracking, and joint torque limits using Quadratic Programming.
Hierarchical Quadratic Programming (QP) for Whole-Body Control
Formulate real-time convex optimization problems that enforce contact friction cones and joint effort limits.
- Task Space Formulation
- Friction Cone Constraints
- QP Solvers (OSQP / qpOASES)
- Operational Space Control
- Whole-body posture stabilization resisting external force pushes in MuJoCo
Phase 3: Sim-to-Real Deep Reinforcement Learning
Train locomotion and manipulation policies in massively parallel physics simulators (NVIDIA Isaac Gym) and transfer to hardware.
Locomotion RL with Isaac Gym & Domain Randomization
Train actor-critic neural networks for robust rough-terrain walking across thousands of parallel humanoid instances with domain randomization.
- PPO (Proximal Policy Optimization)
- Domain Randomization (Mass, Friction, Latency)
- Teacher-Student Distillation
- Sim-to-Real Hardware Transfer
- Bipedal robot parkour policy trained in Isaac Gym and deployed on real robot
Ready to begin Phase 1?
Dive into our free hands-on tutorials and build your first physical prototype.