Before you begin
Starting knowledge
- Comfort with algebra and basic Python.
- Review vectors, trigonometry and derivatives as needed.
Equipment & environment
Use a simple simulated arm or wheeled model. Keep physical experiments optional and supervised.
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 frames and motion
Represent where a robot and an object are without mixing frames or units.
Learn in this order
- Vectors, rotations and homogeneous transforms
- Joint coordinates versus task-space coordinates
- Forward kinematics and numerical checks
Put it into practice
- Draw world, base, tool and camera frames for a simple arm.
- Compute a tool position and compare it with a visualized model.
A frame diagram and a checked forward-kinematics notebook.
Ready for the next step when…
Resources for this stage
Study the mechanics, coordinate frames, kinematics and control foundations relevant to the exercise.
Work through computational robotics examples and compare numerical results with your own calculations.
Intermediate
Study feedback and trajectories
Explain how a controller follows a changing reference under disturbance.
Learn in this order
- Jacobians and local motion relationships
- Reference trajectories and error signals
- Gain effects, saturation and sampling
Put it into practice
- Compare controller settings on the same joint-motion task.
- Introduce a bounded disturbance in simulation and log tracking error.
A controller comparison notebook with labeled plots.
Ready for the next step when…
Resources for this stage
Model physical interactions and test control or learning behavior under explicit simulation assumptions.
Explore dynamics, optimization and model-based analysis for a controlled engineering experiment.
Investigate rigid-body kinematics and dynamics calculations with an explicit robot model.
Professional
Evaluate model limits
Build an analysis that supports a design decision rather than just a formula.
Learn in this order
- Model assumptions and parameter sensitivity
- Constraint handling and actuator limits
- Repeatability and uncertainty reporting
Put it into practice
- Vary mass, friction or latency in a controlled test set.
- Recommend a controller/model combination with documented limitations.
A sensitivity study and a reproducible engineering recommendation.
Ready for the next step when…
Resources for this stage
Explore dynamics, optimization and model-based analysis for a controlled engineering experiment.
Investigate rigid-body kinematics and dynamics calculations with an explicit robot model.
Study the mechanics, coordinate frames, kinematics and control foundations relevant to the exercise.
Common pitfalls
- Learning equations without attaching frames and units.
- Assuming stable simulation proves a physical controller is safe.
Where to go next
Continue to motion planning, actuation or model-based research according to the experiment you want to build.
Explore other learn paths →