Before you begin
Starting knowledge
- Linear algebra, basic dynamics and programming.
- Understand joint limits, state estimation and feedback control.
Equipment & environment
Use simulation first. Physical legged robots require trained supervision, an appropriate test area and fall-management arrangements.
No fixed completion time: use the evidence gates below to decide when to advance. Resource links open the botstest directory entry; check its publisher documentation for the exact version and configuration.
Beginner
Understand the model and balance task
Describe the robot state, contacts and controller objective.
Learn in this order
- Joint coordinates, contacts and inertial parameters
- Support, balance and actuator constraints
- Simulation timestep and reset behavior
Put it into practice
- Load a documented legged model and inspect joints and contacts.
- Run a simple standing or tracking example and log state changes.
An annotated dynamics model and baseline tracking log.
Ready for the next step when…
Resources for this stage
Study the mechanics, coordinate frames, kinematics and control foundations relevant to the exercise.
Model physical interactions and test control or learning behavior under explicit simulation assumptions.
Investigate rigid-body kinematics and dynamics calculations with an explicit robot model.
Intermediate
Train or tune under controlled disturbances
Compare control choices without hiding environmental assumptions.
Learn in this order
- Reward or objective design and unintended behavior
- Domain variation and held-out conditions
- Training seeds, disturbance tests and failure reporting
Put it into practice
- Reproduce a supported learning or control example with saved configuration.
- Test terrain, mass or sensing perturbations separately in simulation.
A controlled locomotion study and a disturbance-result table.
Ready for the next step when…
Resources for this stage
Study a simulation-based robot-learning workflow and preserve the exact environment and training setup.
Explore dynamics, optimization and model-based analysis for a controlled engineering experiment.
Investigate modular research hardware and the engineering requirements of torque-controlled locomotion.
Professional
Plan supervised hardware transfer
Identify the engineering gap between model behavior and a physical trial.
Learn in this order
- Real interface rates, sensing delay and model mismatch
- Actuator, thermal and mechanical constraints
- Operator responsibilities and stop/recovery procedures
Put it into practice
- Prepare a transfer checklist that maps each simulated assumption to hardware evidence.
- Conduct only approved supervised tests within the platform operating limits.
A hardware-transfer dossier and a supervised test/failure log.
Ready for the next step when…
Resources for this stage
Explore a humanoid research configuration; verify development access and plan supervised fall management.
Investigate modular research hardware and the engineering requirements of torque-controlled locomotion.
Inspect recorded robot signals and build views that expose timing and system failures.
Common pitfalls
- Skipping model checks because a pretrained policy moves well in a video.
- Assuming the consumer hardware variant exposes research control interfaces.
Where to go next
Deepen state estimation or actuator engineering when transfer failures reveal a model or hardware limit.
Explore other research paths →