Project overview
This robotics project combines manipulator kinematics, dynamic equations, trajectory generation and controller evaluation in a reproducible MATLAB/Simulink workflow.
The page keeps the primary video, model context, workflow and research interpretation at one stable URL. This helps students and researchers understand what must be modelled, what should be measured and how the study can be extended without relying on screenshots alone.
Recommended simulation workflow
- Define link geometry, masses, joints and coordinate frames
- Derive or import forward/inverse kinematics
- Generate reference trajectories and constraints
- Implement the selected feedback or nonlinear controller
- Compare tracking, torque and robustness under disturbances
Results to extract and compare
Validation checklist
A research-quality implementation should verify units, initial conditions, solver convergence and physical consistency. Use at least one independent reference: an analytical calculation, published data, experimental measurements, a second solver or a validated baseline model. Parameter sweeps should use the same boundary conditions and reporting metrics.
Possible research extensions
- Adaptive or learning control
- Trajectory optimization
- Uncertain payload compensation
- Collision avoidance
- Hardware-in-the-loop preparation
Novelty should be defined as a testable improvement rather than a renamed algorithm. State the baseline, constraints, operating range and statistical or engineering significance of the change.
Typical deliverables
- Editable model and configuration files
- Parameter, material and boundary-condition table
- Validated plots, contours and comparison tables
- Methodology explanation and result interpretation
- Revision support for a proposal, dissertation or journal manuscript
Frequently asked questions
Which software is used for this project?
The video is presented with Engineering simulation software. Confirm the exact version, add-ons and solver settings before reproducing the model.
Which results should be validated?
Joint-position and velocity tracking, Cartesian end-effector path, Control torque and effort, Settling time and overshoot and Robustness to payload and parameter variation. Use units, common operating cases and an error or convergence measure.
How can the work be extended for PhD research?
Possible extensions include adaptive or learning control, trajectory optimization, uncertain payload compensation, collision avoidance and hardware-in-the-loop preparation. The contribution should be measurable and compared with a reproducible baseline.
